初始化项目，由ModelHub XC社区提供模型

Model: kosa-labs/kosa-4B-it-v1
Source: Original Platform

.gitattributes

@@ -0,0 +1,39 @@
+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+gguf/kosa-4B-it-v1-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+gguf/kosa-4B-it-v1-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+gguf/kosa-4B-it-v1-Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,56 @@
+---
+base_model: Qwen/Qwen3-4B-Instruct-2507
+license: apache-2.0
+pipeline_tag: text-generation
+language:
+- en
+tags:
+- qwen3
+- instruct
+---
+# kosa-4B-it-v1
+
+An instruction-tuned model built on Qwen/Qwen3-4B-Instruct-2507 using the Kosa Method. Kosa Labs is a UK-based independent lab.
+
+## Benchmarks
+
+| Benchmark | Qwen3-4B-Instruct-2507 | kosa-4B-it-v1 |
+|---|---:|---:|
+| GSM8K (strict) | 73.24% | 84.23% |
+| GSM8K (flexible) | 79.15% | 85.60% |
+| IFEval (prompt strict) | 83.36% | 85.77% |
+| IFEval (instruction strict) | 88.61% | 90.29% |
+| ARC-Challenge (acc_norm) | 43.09% | 52.13% |
+| MMLU | 61.89% | 65.76% |
+| **Average** | **71.56%** | **77.30%** |
+
+Both models evaluated in the same session with identical settings: lm-evaluation-harness 0.4.12, vLLM, bfloat16, temperature 0, chat template applied. Raw result files in /benchmarks. Training data verified clean against all four benchmark test sets (13-gram and 8-gram overlap checks with positive-control validation).
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = "kosa-labs/kosa-4B-it-v1"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+
+messages = [{"role": "user", "content": "Write a concise project update."}]
+inputs = tokenizer.apply_chat_template(
+    messages,
+    add_generation_prompt=True,
+    return_tensors="pt",
+).to(model.device)
+outputs = model.generate(inputs, max_new_tokens=256)
+print(tokenizer.decode(outputs[0][inputs.shape[-1]:], skip_special_tokens=True))
+```
+
+GGUF quantizations are available in /gguf:
+- gguf/kosa-4B-it-v1-Q4_K_M.gguf
+- gguf/kosa-4B-it-v1-Q5_K_M.gguf
+- gguf/kosa-4B-it-v1-Q8_0.gguf

benchmarks/arc_challenge_base.json

@@ -0,0 +1,136 @@
+{
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if message.content is string %}\n        {%- set content = message.content %}\n    {%- else %}\n        {%- set content = '' %}\n    {%- endif %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}",
+  "chat_template_sha": "64f85b198065d0fba2a81f37e10ed68161ce2c19a754c7100e67e0ca2ee9c326",
+  "config": {
+    "batch_size": "32",
+    "batch_sizes": [],
+    "bootstrap_iters": 100000,
+    "device": "cuda:0",
+    "fewshot_seed": 1234,
+    "gen_kwargs": {},
+    "limit": null,
+    "model": "hf",
+    "model_args": "pretrained=Qwen/Qwen3-4B-Instruct-2507",
+    "model_dtype": "torch.bfloat16",
+    "model_num_parameters": 4022468096,
+    "model_revision": "main",
+    "model_sha": "cdbee75f17c01a7cc42f958dc650907174af0554",
+    "numpy_seed": 1234,
+    "random_seed": 0,
+    "torch_seed": 1234,
+    "use_cache": "[redacted]"
+  },
+  "configs": {
+    "arc_challenge": {
+      "dataset_name": "ARC-Challenge",
+      "dataset_path": "allenai/ai2_arc",
+      "description": "",
+      "doc_to_choice": "{{choices.text}}",
+      "doc_to_decontamination_query": "Question: {{question}}\nAnswer:",
+      "doc_to_target": "{{choices.label.index(answerKey)}}",
+      "doc_to_text": "Question: {{question}}\nAnswer:",
+      "fewshot_config": {
+        "doc_to_choice": "{{choices.text}}",
+        "doc_to_target": "{{choices.label.index(answerKey)}}",
+        "doc_to_text": "Question: {{question}}\nAnswer:",
+        "fewshot_delimiter": "\n\n",
+        "fewshot_indices": null,
+        "gen_prefix": null,
+        "process_docs": null,
+        "sampler": "default",
+        "samples": null,
+        "split": null,
+        "target_delimiter": " "
+      },
+      "fewshot_delimiter": "\n\n",
+      "metadata": {
+        "config_source": "[redacted]",
+        "dtype": "bfloat16",
+        "pretrained": "Qwen/Qwen3-4B-Instruct-2507",
+        "trust_remote_code": true,
+        "version": 1.0
+      },
+      "metric_list": [
+        {
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "metric": "acc"
+        },
+        {
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "metric": "acc_norm"
+        }
+      ],
+      "num_fewshot": 0,
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": true,
+      "target_delimiter": " ",
+      "task": "arc_challenge",
+      "test_split": "test",
+      "training_split": "train",
+      "unsafe_code": false,
+      "validation_split": "validation"
+    }
+  },
+  "date": 1780955961.7944982,
+  "eot_token_id": 151645,
+  "fewshot_as_multiturn": true,
+  "git_hash": null,
+  "group_subtasks": {},
+  "higher_is_better": {
+    "arc_challenge": {
+      "acc": true,
+      "acc_norm": true
+    }
+  },
+  "lm_eval_version": "0.4.12",
+  "max_length": 262144,
+  "model_name": "Qwen/Qwen3-4B-Instruct-2507",
+  "model_name_sanitized": "Qwen/Qwen3-4B-Instruct-2507",
+  "model_source": "Qwen/Qwen3-4B-Instruct-2507",
+  "n-samples": {
+    "arc_challenge": {
+      "effective": 1172,
+      "original": 1172
+    }
+  },
+  "n-shot": {
+    "arc_challenge": 0
+  },
+  "results": {
+    "arc_challenge": {
+      "acc,none": 0.4334470989761092,
+      "acc_norm,none": 0.4308873720136519,
+      "acc_norm_stderr,none": 0.014471133392642476,
+      "acc_stderr,none": 0.014481376224558896,
+      "alias": "arc_challenge",
+      "name": "arc_challenge",
+      "sample_len": 1172
+    }
+  },
+  "system_instruction": null,
+  "system_instruction_sha": null,
+  "task_hashes": {
+    "arc_challenge": "9bcbbcee5924b2d8d096f81544b8e32c71e63704d363e292090ad1ba91968f5a"
+  },
+  "tokenizer_bos_token": [
+    null,
+    "None"
+  ],
+  "tokenizer_eos_token": [
+    "<|im_end|>",
+    "151645"
+  ],
+  "tokenizer_pad_token": [
+    "<|endoftext|>",
+    "151643"
+  ],
+  "total_evaluation_time_seconds": "212.6989970318973",
+  "transformers_version": "4.57.6",
+  "upper_git_hash": null,
+  "versions": {
+    "arc_challenge": 1.0
+  }
+}

benchmarks/arc_challenge_kosa.json

@@ -0,0 +1,134 @@
+{
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if message.content is string %}\n        {%- set content = message.content %}\n    {%- else %}\n        {%- set content = '' %}\n    {%- endif %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}",
+  "chat_template_sha": "64f85b198065d0fba2a81f37e10ed68161ce2c19a754c7100e67e0ca2ee9c326",
+  "config": {
+    "batch_size": "32",
+    "batch_sizes": [],
+    "bootstrap_iters": 100000,
+    "device": "cuda:0",
+    "fewshot_seed": 1234,
+    "gen_kwargs": {},
+    "limit": null,
+    "model": "vllm",
+    "model_args": "pretrained=kosa-labs/kosa-4B-it-v1",
+    "numpy_seed": 1234,
+    "random_seed": 0,
+    "torch_seed": 1234,
+    "use_cache": "[redacted]"
+  },
+  "configs": {
+    "arc_challenge": {
+      "dataset_name": "ARC-Challenge",
+      "dataset_path": "allenai/ai2_arc",
+      "description": "",
+      "doc_to_choice": "{{choices.text}}",
+      "doc_to_decontamination_query": "Question: {{question}}\nAnswer:",
+      "doc_to_target": "{{choices.label.index(answerKey)}}",
+      "doc_to_text": "Question: {{question}}\nAnswer:",
+      "fewshot_config": {
+        "doc_to_choice": "{{choices.text}}",
+        "doc_to_target": "{{choices.label.index(answerKey)}}",
+        "doc_to_text": "Question: {{question}}\nAnswer:",
+        "fewshot_delimiter": "\n\n",
+        "fewshot_indices": null,
+        "gen_prefix": null,
+        "process_docs": null,
+        "sampler": "default",
+        "samples": null,
+        "split": null,
+        "target_delimiter": " "
+      },
+      "fewshot_delimiter": "\n\n",
+      "metadata": {
+        "config_source": "[redacted]",
+        "dtype": "bfloat16",
+        "gpu_memory_utilization": 0.82,
+        "pretrained": "[redacted]",
+        "tensor_parallel_size": 1,
+        "trust_remote_code": true,
+        "version": 1.0
+      },
+      "metric_list": [
+        {
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "metric": "acc"
+        },
+        {
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "metric": "acc_norm"
+        }
+      ],
+      "num_fewshot": 0,
+      "output_type": "multiple_choice",
+      "repeats": 1,
+      "should_decontaminate": true,
+      "target_delimiter": " ",
+      "task": "arc_challenge",
+      "test_split": "test",
+      "training_split": "train",
+      "unsafe_code": false,
+      "validation_split": "validation"
+    }
+  },
+  "date": 1781168624.8804162,
+  "eot_token_id": 151645,
+  "fewshot_as_multiturn": true,
+  "git_hash": null,
+  "group_subtasks": {},
+  "higher_is_better": {
+    "arc_challenge": {
+      "acc": true,
+      "acc_norm": true
+    }
+  },
+  "lm_eval_version": "0.4.12",
+  "max_length": 262144,
+  "model_name": "kosa-labs/kosa-4B-it-v1",
+  "model_name_sanitized": "kosa-labs/kosa-4B-it-v1",
+  "model_source": "kosa-labs/kosa-4B-it-v1",
+  "n-samples": {
+    "arc_challenge": {
+      "effective": 1172,
+      "original": 1172
+    }
+  },
+  "n-shot": {
+    "arc_challenge": 0
+  },
+  "results": {
+    "arc_challenge": {
+      "acc,none": 0.5315699658703071,
+      "acc_norm,none": 0.5213310580204779,
+      "acc_norm_stderr,none": 0.014598087973127125,
+      "acc_stderr,none": 0.014582236460866984,
+      "alias": "arc_challenge",
+      "name": "arc_challenge",
+      "sample_len": 1172
+    }
+  },
+  "system_instruction": null,
+  "system_instruction_sha": null,
+  "task_hashes": {
+    "arc_challenge": "9bcbbcee5924b2d8d096f81544b8e32c71e63704d363e292090ad1ba91968f5a"
+  },
+  "tokenizer_bos_token": [
+    null,
+    "None"
+  ],
+  "tokenizer_eos_token": [
+    "<|im_end|>",
+    "151645"
+  ],
+  "tokenizer_pad_token": [
+    "<|endoftext|>",
+    "151643"
+  ],
+  "total_evaluation_time_seconds": "334.5368347261101",
+  "transformers_version": "5.11.0",
+  "upper_git_hash": null,
+  "versions": {
+    "arc_challenge": 1.0
+  }
+}

benchmarks/cross_model_comparison_summary.json

@@ -0,0 +1,170 @@
+{
+  "backend_settings": {
+    "apply_chat_template": true,
+    "backend": "vllm",
+    "batch_size": 32,
+    "dtype": "bfloat16",
+    "gpu_memory_utilization": 0.82,
+    "seed": "0,1234,1234,1234",
+    "temperature": "task-default 0",
+    "tensor_parallel_size": 1
+  },
+  "benchmark_files": {
+    "base": [
+      "gsm8k_base.json",
+      "ifeval_base.json",
+      "arc_challenge_base.json",
+      "mmlu_base.json"
+    ],
+    "kosa": [
+      "gsm8k_kosa.json",
+      "ifeval_kosa.json",
+      "arc_challenge_kosa.json",
+      "mmlu_kosa.json"
+    ]
+  },
+  "date": "2026-06-11T11:17:13.383746+00:00",
+  "harness": "lm-evaluation-harness 0.4.12",
+  "scored_rows": [
+    {
+      "arc_acc_norm": 0.5213310580204779,
+      "avg5": 0.7960271980535851,
+      "avg6": 0.7729557704902223,
+      "display_avg": 0.7729557704902223,
+      "display_avg_kind": "avg6",
+      "downloads": null,
+      "group": "kosa",
+      "gsm8k_flex": 0.8559514783927218,
+      "gsm8k_strict": 0.8423047763457164,
+      "ifeval_inst": 0.9028776978417267,
+      "ifeval_prompt": 0.8576709796672828,
+      "mmlu": 0.6575986326734083,
+      "mmlu_humanities": 0.5883103081827843,
+      "mmlu_other": 0.7219182491149019,
+      "mmlu_social": 0.7897302567435814,
+      "mmlu_stem": 0.5686647637170948,
+      "model": "kosa-labs/kosa-4B-it-v1",
+      "status": "scored"
+    },
+    {
+      "arc_acc_norm": 0.5170648464163823,
+      "avg5": 0.7854459095088681,
+      "avg6": 0.766511860924579,
+      "display_avg": 0.766511860924579,
+      "display_avg_kind": "avg6",
+      "downloads": 798,
+      "group": "same-base genuine accessible",
+      "gsm8k_flex": 0.8688400303260045,
+      "gsm8k_strict": 0.8483699772554966,
+      "ifeval_inst": 0.8741007194244604,
+      "ifeval_prompt": 0.8188539741219963,
+      "mmlu": 0.6718416180031335,
+      "mmlu_humanities": 0.6063761955366631,
+      "mmlu_other": 0.7296427421950434,
+      "mmlu_social": 0.7955801104972375,
+      "mmlu_stem": 0.5918173168411037,
+      "model": "codingmonster1234/chess-sft-modelv2",
+      "status": "scored"
+    },
+    {
+      "arc_acc_norm": 0.5366894197952219,
+      "avg5": 0.7610974365380638,
+      "avg6": null,
+      "display_avg": 0.7610974365380638,
+      "display_avg_kind": "avg5",
+      "downloads": 3126,
+      "group": "same-base genuine accessible",
+      "gsm8k_flex": 0.8233510235026535,
+      "gsm8k_strict": 0.8218347232752085,
+      "ifeval_inst": 0.841726618705036,
+      "ifeval_prompt": 0.7818853974121996,
+      "model": "Applied-Innovation-Center/Karnak-6B-v1.0",
+      "status": "scored"
+    },
+    {
+      "arc_acc_norm": 0.42918088737201365,
+      "avg5": 0.7317990152643855,
+      "avg6": null,
+      "display_avg": 0.7317990152643855,
+      "display_avg_kind": "avg5",
+      "downloads": 28076,
+      "group": "previous same-base row",
+      "gsm8k_flex": 0.7907505686125853,
+      "gsm8k_strict": 0.7278241091736164,
+      "ifeval_inst": 0.8812949640287769,
+      "ifeval_prompt": 0.8299445471349353,
+      "model": "unsloth/Qwen3-4B-Instruct-2507",
+      "status": "scored; excluded from genuine verdict"
+    },
+    {
+      "arc_acc_norm": 0.5204778156996587,
+      "avg5": 0.7256165583147159,
+      "avg6": null,
+      "display_avg": 0.7256165583147159,
+      "display_avg_kind": "avg5",
+      "downloads": 1194286,
+      "group": "cross-family",
+      "gsm8k_flex": 0.8233510235026535,
+      "gsm8k_strict": 0.819560272934041,
+      "ifeval_inst": 0.7733812949640287,
+      "ifeval_prompt": 0.6913123844731978,
+      "model": "microsoft/Phi-4-mini-instruct",
+      "status": "scored"
+    },
+    {
+      "arc_acc_norm": 0.4308873720136519,
+      "avg5": 0.7349003265000296,
+      "avg6": 0.7155717600005587,
+      "display_avg": 0.7155717600005587,
+      "display_avg_kind": "avg6",
+      "downloads": null,
+      "group": "base",
+      "gsm8k_flex": 0.7915087187263078,
+      "gsm8k_strict": 0.7323730098559514,
+      "ifeval_inst": 0.8860911270983214,
+      "ifeval_prompt": 0.833641404805915,
+      "mmlu": 0.6189289275032047,
+      "mmlu_humanities": 0.5596174282678003,
+      "mmlu_other": 0.6903765690376569,
+      "mmlu_social": 0.7565810854728632,
+      "mmlu_stem": 0.5026958452267681,
+      "model": "Qwen/Qwen3-4B-Instruct-2507",
+      "status": "scored"
+    },
+    {
+      "arc_acc_norm": 0.4906143344709898,
+      "avg5": 0.6892628966189842,
+      "avg6": null,
+      "display_avg": 0.6892628966189842,
+      "display_avg_kind": "avg5",
+      "downloads": 1530,
+      "group": "same-base genuine accessible",
+      "gsm8k_flex": 0.778620166793025,
+      "gsm8k_strict": 0.5981804397270659,
+      "ifeval_inst": 0.8321342925659473,
+      "ifeval_prompt": 0.7467652495378928,
+      "model": "RefalMachine/RuadaptQwen3-4B-Instruct",
+      "status": "scored"
+    },
+    {
+      "arc_acc_norm": 0.5452218430034129,
+      "avg5": 0.7978064681913222,
+      "avg6": 0.775874663292417,
+      "display_avg": 0.775874663292417,
+      "display_avg_kind": "avg6",
+      "downloads": null,
+      "group": "merge candidate",
+      "gsm8k_flex": 0.8635329795299469,
+      "gsm8k_strict": 0.8514025777103866,
+      "ifeval_inst": 0.8896882494004796,
+      "ifeval_prompt": 0.8391866913123844,
+      "mmlu": 0.666215638797892,
+      "mmlu_humanities": 0.5957492029755579,
+      "mmlu_other": 0.7257804956549726,
+      "mmlu_social": 0.7923301917452064,
+      "mmlu_stem": 0.5895972090072946,
+      "model": "merge:iter1_ta4_cat_t30",
+      "status": "scored; full-size merge winner eval; incumbent anchor wins tie"
+    }
+  ]
+}

benchmarks/gsm8k_base.json

@@ -0,0 +1,172 @@
+{
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if message.content is string %}\n        {%- set content = message.content %}\n    {%- else %}\n        {%- set content = '' %}\n    {%- endif %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}",
+  "chat_template_sha": "64f85b198065d0fba2a81f37e10ed68161ce2c19a754c7100e67e0ca2ee9c326",
+  "config": {
+    "batch_size": "32",
+    "batch_sizes": [],
+    "bootstrap_iters": 100000,
+    "device": "cuda:0",
+    "fewshot_seed": 1234,
+    "gen_kwargs": {},
+    "limit": null,
+    "model": "hf",
+    "model_args": "pretrained=Qwen/Qwen3-4B-Instruct-2507",
+    "model_dtype": "torch.bfloat16",
+    "model_num_parameters": 4022468096,
+    "model_revision": "main",
+    "model_sha": "cdbee75f17c01a7cc42f958dc650907174af0554",
+    "numpy_seed": 1234,
+    "random_seed": 0,
+    "torch_seed": 1234,
+    "use_cache": "[redacted]"
+  },
+  "configs": {
+    "gsm8k": {
+      "dataset_name": "main",
+      "dataset_path": "openai/gsm8k",
+      "description": "",
+      "doc_to_target": "{{answer}}",
+      "doc_to_text": "Question: {{question}}\nAnswer:",
+      "fewshot_config": {
+        "doc_to_choice": null,
+        "doc_to_target": "{{answer}}",
+        "doc_to_text": "Question: {{question}}\nAnswer:",
+        "fewshot_delimiter": "\n\n",
+        "fewshot_indices": null,
+        "gen_prefix": null,
+        "process_docs": null,
+        "sampler": "default",
+        "samples": null,
+        "split": "train",
+        "target_delimiter": " "
+      },
+      "fewshot_delimiter": "\n\n",
+      "fewshot_split": "train",
+      "filter_list": [
+        {
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "#### (\\-?[0-9\\.\\,]+)"
+            },
+            {
+              "function": "take_first"
+            }
+          ],
+          "name": "strict-match"
+        },
+        {
+          "filter": [
+            {
+              "function": "regex",
+              "group_select": -1,
+              "regex_pattern": "(-?[$0-9.,]{2,})|(-?[0-9]+)"
+            },
+            {
+              "function": "take_first"
+            }
+          ],
+          "name": "flexible-extract"
+        }
+      ],
+      "generation_kwargs": {
+        "do_sample": false,
+        "temperature": 0.0,
+        "until": [
+          "Question:",
+          "</s>",
+          "<|im_end|>"
+        ]
+      },
+      "metadata": {
+        "config_source": "[redacted]",
+        "dtype": "bfloat16",
+        "pretrained": "Qwen/Qwen3-4B-Instruct-2507",
+        "trust_remote_code": true,
+        "version": 3.0
+      },
+      "metric_list": [
+        {
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": false,
+          "metric": "exact_match",
+          "regexes_to_ignore": [
+            ",",
+            "\\$",
+            "(?s).*#### ",
+            "\\.$"
+          ]
+        }
+      ],
+      "num_fewshot": 5,
+      "output_type": "generate_until",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "target_delimiter": " ",
+      "task": "gsm8k",
+      "test_split": "test",
+      "training_split": "train",
+      "unsafe_code": false
+    }
+  },
+  "date": 1780942857.9108624,
+  "eot_token_id": 151645,
+  "fewshot_as_multiturn": true,
+  "git_hash": null,
+  "group_subtasks": {},
+  "higher_is_better": {
+    "gsm8k": {
+      "exact_match": true
+    }
+  },
+  "lm_eval_version": "0.4.12",
+  "max_length": 262144,
+  "model_name": "Qwen/Qwen3-4B-Instruct-2507",
+  "model_name_sanitized": "Qwen/Qwen3-4B-Instruct-2507",
+  "model_source": "Qwen/Qwen3-4B-Instruct-2507",
+  "n-samples": {
+    "gsm8k": {
+      "effective": 1319,
+      "original": 1319
+    }
+  },
+  "n-shot": {
+    "gsm8k": 5
+  },
+  "results": {
+    "gsm8k": {
+      "alias": "gsm8k",
+      "exact_match,flexible-extract": 0.7915087187263078,
+      "exact_match,strict-match": 0.7323730098559514,
+      "exact_match_stderr,flexible-extract": 0.01118958798579141,
+      "exact_match_stderr,strict-match": 0.012194764427053348,
+      "name": "gsm8k",
+      "sample_len": 1319
+    }
+  },
+  "system_instruction": null,
+  "system_instruction_sha": null,
+  "task_hashes": {
+    "gsm8k": "57f6f099e46d41808275113fe524b6af081154f7c87fa7826e3dd1775f468206"
+  },
+  "tokenizer_bos_token": [
+    null,
+    "None"
+  ],
+  "tokenizer_eos_token": [
+    "<|im_end|>",
+    "151645"
+  ],
+  "tokenizer_pad_token": [
+    "<|endoftext|>",
+    "151643"
+  ],
+  "total_evaluation_time_seconds": "1433.1546569541097",
+  "transformers_version": "4.57.6",
+  "upper_git_hash": null,
+  "versions": {
+    "gsm8k": 3.0
+  }
+}

benchmarks/gsm8k_kosa.json

@@ -0,0 +1,170 @@
+{
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if message.content is string %}\n        {%- set content = message.content %}\n    {%- else %}\n        {%- set content = '' %}\n    {%- endif %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}",
+  "chat_template_sha": "64f85b198065d0fba2a81f37e10ed68161ce2c19a754c7100e67e0ca2ee9c326",
+  "config": {
+    "batch_size": "32",
+    "batch_sizes": [],
+    "bootstrap_iters": 100000,
+    "device": "cuda:0",
+    "fewshot_seed": 1234,
+    "gen_kwargs": {},
+    "limit": null,
+    "model": "vllm",
+    "model_args": "pretrained=kosa-labs/kosa-4B-it-v1",
+    "numpy_seed": 1234,
+    "random_seed": 0,
+    "torch_seed": 1234,
+    "use_cache": "[redacted]"
+  },
+  "configs": {
+    "gsm8k": {
+      "dataset_name": "main",
+      "dataset_path": "openai/gsm8k",
+      "description": "",
+      "doc_to_target": "{{answer}}",
+      "doc_to_text": "Question: {{question}}\nAnswer:",
+      "fewshot_config": {
+        "doc_to_choice": null,
+        "doc_to_target": "{{answer}}",
+        "doc_to_text": "Question: {{question}}\nAnswer:",
+        "fewshot_delimiter": "\n\n",
+        "fewshot_indices": null,
+        "gen_prefix": null,
+        "process_docs": null,
+        "sampler": "default",
+        "samples": null,
+        "split": "train",
+        "target_delimiter": " "
+      },
+      "fewshot_delimiter": "\n\n",
+      "fewshot_split": "train",
+      "filter_list": [
+        {
+          "filter": [
+            {
+              "function": "regex",
+              "regex_pattern": "#### (\\-?[0-9\\.\\,]+)"
+            },
+            {
+              "function": "take_first"
+            }
+          ],
+          "name": "strict-match"
+        },
+        {
+          "filter": [
+            {
+              "function": "regex",
+              "group_select": -1,
+              "regex_pattern": "(-?[$0-9.,]{2,})|(-?[0-9]+)"
+            },
+            {
+              "function": "take_first"
+            }
+          ],
+          "name": "flexible-extract"
+        }
+      ],
+      "generation_kwargs": {
+        "do_sample": false,
+        "temperature": 0.0,
+        "until": [
+          "Question:",
+          "</s>",
+          "<|im_end|>"
+        ]
+      },
+      "metadata": {
+        "config_source": "[redacted]",
+        "dtype": "bfloat16",
+        "gpu_memory_utilization": 0.82,
+        "pretrained": "[redacted]",
+        "tensor_parallel_size": 1,
+        "trust_remote_code": true,
+        "version": 3.0
+      },
+      "metric_list": [
+        {
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "ignore_case": true,
+          "ignore_punctuation": false,
+          "metric": "exact_match",
+          "regexes_to_ignore": [
+            ",",
+            "\\$",
+            "(?s).*#### ",
+            "\\.$"
+          ]
+        }
+      ],
+      "num_fewshot": 5,
+      "output_type": "generate_until",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "target_delimiter": " ",
+      "task": "gsm8k",
+      "test_split": "test",
+      "training_split": "train",
+      "unsafe_code": false
+    }
+  },
+  "date": 1781168624.8804162,
+  "eot_token_id": 151645,
+  "fewshot_as_multiturn": true,
+  "git_hash": null,
+  "group_subtasks": {},
+  "higher_is_better": {
+    "gsm8k": {
+      "exact_match": true
+    }
+  },
+  "lm_eval_version": "0.4.12",
+  "max_length": 262144,
+  "model_name": "kosa-labs/kosa-4B-it-v1",
+  "model_name_sanitized": "kosa-labs/kosa-4B-it-v1",
+  "model_source": "kosa-labs/kosa-4B-it-v1",
+  "n-samples": {
+    "gsm8k": {
+      "effective": 1319,
+      "original": 1319
+    }
+  },
+  "n-shot": {
+    "gsm8k": 5
+  },
+  "results": {
+    "gsm8k": {
+      "alias": "gsm8k",
+      "exact_match,flexible-extract": 0.8559514783927218,
+      "exact_match,strict-match": 0.8423047763457164,
+      "exact_match_stderr,flexible-extract": 0.009672110973065284,
+      "exact_match_stderr,strict-match": 0.010038901575061383,
+      "name": "gsm8k",
+      "sample_len": 1319
+    }
+  },
+  "system_instruction": null,
+  "system_instruction_sha": null,
+  "task_hashes": {
+    "gsm8k": "57f6f099e46d41808275113fe524b6af081154f7c87fa7826e3dd1775f468206"
+  },
+  "tokenizer_bos_token": [
+    null,
+    "None"
+  ],
+  "tokenizer_eos_token": [
+    "<|im_end|>",
+    "151645"
+  ],
+  "tokenizer_pad_token": [
+    "<|endoftext|>",
+    "151643"
+  ],
+  "total_evaluation_time_seconds": "334.5368347261101",
+  "transformers_version": "5.11.0",
+  "upper_git_hash": null,
+  "versions": {
+    "gsm8k": 3.0
+  }
+}

benchmarks/ifeval_base.json

@@ -0,0 +1,154 @@
+{
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if message.content is string %}\n        {%- set content = message.content %}\n    {%- else %}\n        {%- set content = '' %}\n    {%- endif %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}",
+  "chat_template_sha": "64f85b198065d0fba2a81f37e10ed68161ce2c19a754c7100e67e0ca2ee9c326",
+  "config": {
+    "batch_size": "16",
+    "batch_sizes": [],
+    "bootstrap_iters": 100000,
+    "device": "cuda:0",
+    "fewshot_seed": 1234,
+    "gen_kwargs": {},
+    "limit": null,
+    "model": "hf",
+    "model_args": "pretrained=Qwen/Qwen3-4B-Instruct-2507",
+    "model_dtype": "torch.bfloat16",
+    "model_num_parameters": 4022468096,
+    "model_revision": "main",
+    "model_sha": "cdbee75f17c01a7cc42f958dc650907174af0554",
+    "numpy_seed": 1234,
+    "random_seed": 0,
+    "torch_seed": 1234,
+    "use_cache": "[redacted]"
+  },
+  "configs": {
+    "ifeval": {
+      "dataset_path": "google/IFEval",
+      "description": "",
+      "doc_to_target": 0,
+      "doc_to_text": "prompt",
+      "fewshot_config": {
+        "doc_to_choice": null,
+        "doc_to_target": 0,
+        "doc_to_text": "prompt",
+        "fewshot_delimiter": "\n\n",
+        "fewshot_indices": null,
+        "gen_prefix": null,
+        "process_docs": null,
+        "sampler": "default",
+        "samples": null,
+        "split": null,
+        "target_delimiter": " "
+      },
+      "fewshot_delimiter": "\n\n",
+      "generation_kwargs": {
+        "do_sample": false,
+        "max_gen_toks": 1280,
+        "temperature": 0.0,
+        "until": []
+      },
+      "metadata": {
+        "config_source": "[redacted]",
+        "dtype": "bfloat16",
+        "pretrained": "Qwen/Qwen3-4B-Instruct-2507",
+        "trust_remote_code": true,
+        "version": 4.0
+      },
+      "metric_list": [
+        {
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "metric": "prompt_level_strict_acc"
+        },
+        {
+          "aggregation": "def agg_inst_level_acc(items):\n    flat_items = [item for sublist in items for item in sublist]\n    inst_level_acc = sum(flat_items) / len(flat_items)\n    return inst_level_acc\n",
+          "higher_is_better": true,
+          "metric": "inst_level_strict_acc"
+        },
+        {
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "metric": "prompt_level_loose_acc"
+        },
+        {
+          "aggregation": "def agg_inst_level_acc(items):\n    flat_items = [item for sublist in items for item in sublist]\n    inst_level_acc = sum(flat_items) / len(flat_items)\n    return inst_level_acc\n",
+          "higher_is_better": true,
+          "metric": "inst_level_loose_acc"
+        }
+      ],
+      "num_fewshot": 0,
+      "output_type": "generate_until",
+      "process_results": "def process_results(doc, results):\n    inp = InputExample(\n        key=doc[\"key\"],\n        instruction_id_list=doc[\"instruction_id_list\"],\n        prompt=doc[\"prompt\"],\n        kwargs=doc[\"kwargs\"],\n    )\n    response = results[0]\n\n    out_strict = test_instruction_following_strict(inp, response)\n    out_loose = test_instruction_following_loose(inp, response)\n\n    return {\n        \"prompt_level_strict_acc\": out_strict.follow_all_instructions,\n        \"inst_level_strict_acc\": out_strict.follow_instruction_list,\n        \"prompt_level_loose_acc\": out_loose.follow_all_instructions,\n        \"inst_level_loose_acc\": out_loose.follow_instruction_list,\n    }\n",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "target_delimiter": " ",
+      "task": "ifeval",
+      "test_split": "train",
+      "unsafe_code": false
+    }
+  },
+  "date": 1780940963.7622316,
+  "eot_token_id": 151645,
+  "fewshot_as_multiturn": true,
+  "git_hash": null,
+  "group_subtasks": {},
+  "higher_is_better": {
+    "ifeval": {
+      "inst_level_loose_acc": true,
+      "inst_level_strict_acc": true,
+      "prompt_level_loose_acc": true,
+      "prompt_level_strict_acc": true
+    }
+  },
+  "lm_eval_version": "0.4.12",
+  "max_length": 262144,
+  "model_name": "Qwen/Qwen3-4B-Instruct-2507",
+  "model_name_sanitized": "Qwen/Qwen3-4B-Instruct-2507",
+  "model_source": "Qwen/Qwen3-4B-Instruct-2507",
+  "n-samples": {
+    "ifeval": {
+      "effective": 541,
+      "original": 541
+    }
+  },
+  "n-shot": {
+    "ifeval": 0
+  },
+  "results": {
+    "ifeval": {
+      "alias": "ifeval",
+      "inst_level_loose_acc,none": 0.9064748201438849,
+      "inst_level_loose_acc_stderr,none": "N/A",
+      "inst_level_strict_acc,none": 0.8860911270983214,
+      "inst_level_strict_acc_stderr,none": "N/A",
+      "name": "ifeval",
+      "prompt_level_loose_acc,none": 0.8650646950092421,
+      "prompt_level_loose_acc_stderr,none": 0.014702466942017852,
+      "prompt_level_strict_acc,none": 0.833641404805915,
+      "prompt_level_strict_acc_stderr,none": 0.016025639930548306,
+      "sample_len": 541
+    }
+  },
+  "system_instruction": null,
+  "system_instruction_sha": null,
+  "task_hashes": {
+    "ifeval": "e01bec2e716639c6aa89facb027f54c1a8238f533e9488cbce6f5a79ae309c3d"
+  },
+  "tokenizer_bos_token": [
+    null,
+    "None"
+  ],
+  "tokenizer_eos_token": [
+    "<|im_end|>",
+    "151645"
+  ],
+  "tokenizer_pad_token": [
+    "<|endoftext|>",
+    "151643"
+  ],
+  "total_evaluation_time_seconds": "1874.040236396715",
+  "transformers_version": "4.57.6",
+  "upper_git_hash": null,
+  "versions": {
+    "ifeval": 4.0
+  }
+}

benchmarks/ifeval_kosa.json

@@ -0,0 +1,152 @@
+{
+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n    {%- if message.content is string %}\n        {%- set content = message.content %}\n    {%- else %}\n        {%- set content = '' %}\n    {%- endif %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}",
+  "chat_template_sha": "64f85b198065d0fba2a81f37e10ed68161ce2c19a754c7100e67e0ca2ee9c326",
+  "config": {
+    "batch_size": "32",
+    "batch_sizes": [],
+    "bootstrap_iters": 100000,
+    "device": "cuda:0",
+    "fewshot_seed": 1234,
+    "gen_kwargs": {},
+    "limit": null,
+    "model": "vllm",
+    "model_args": "pretrained=kosa-labs/kosa-4B-it-v1",
+    "numpy_seed": 1234,
+    "random_seed": 0,
+    "torch_seed": 1234,
+    "use_cache": "[redacted]"
+  },
+  "configs": {
+    "ifeval": {
+      "dataset_path": "google/IFEval",
+      "description": "",
+      "doc_to_target": 0,
+      "doc_to_text": "prompt",
+      "fewshot_config": {
+        "doc_to_choice": null,
+        "doc_to_target": 0,
+        "doc_to_text": "prompt",
+        "fewshot_delimiter": "\n\n",
+        "fewshot_indices": null,
+        "gen_prefix": null,
+        "process_docs": null,
+        "sampler": "default",
+        "samples": null,
+        "split": null,
+        "target_delimiter": " "
+      },
+      "fewshot_delimiter": "\n\n",
+      "generation_kwargs": {
+        "do_sample": false,
+        "max_gen_toks": 1280,
+        "temperature": 0.0,
+        "until": []
+      },
+      "metadata": {
+        "config_source": "[redacted]",
+        "dtype": "bfloat16",
+        "gpu_memory_utilization": 0.82,
+        "pretrained": "[redacted]",
+        "tensor_parallel_size": 1,
+        "trust_remote_code": true,
+        "version": 4.0
+      },
+      "metric_list": [
+        {
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "metric": "prompt_level_strict_acc"
+        },
+        {
+          "aggregation": "def agg_inst_level_acc(items):\n    flat_items = [item for sublist in items for item in sublist]\n    inst_level_acc = sum(flat_items) / len(flat_items)\n    return inst_level_acc\n",
+          "higher_is_better": true,
+          "metric": "inst_level_strict_acc"
+        },
+        {
+          "aggregation": "mean",
+          "higher_is_better": true,
+          "metric": "prompt_level_loose_acc"
+        },
+        {
+          "aggregation": "def agg_inst_level_acc(items):\n    flat_items = [item for sublist in items for item in sublist]\n    inst_level_acc = sum(flat_items) / len(flat_items)\n    return inst_level_acc\n",
+          "higher_is_better": true,
+          "metric": "inst_level_loose_acc"
+        }
+      ],
+      "num_fewshot": 0,
+      "output_type": "generate_until",
+      "process_results": "def process_results(doc, results):\n    inp = InputExample(\n        key=doc[\"key\"],\n        instruction_id_list=doc[\"instruction_id_list\"],\n        prompt=doc[\"prompt\"],\n        kwargs=doc[\"kwargs\"],\n    )\n    response = results[0]\n\n    out_strict = test_instruction_following_strict(inp, response)\n    out_loose = test_instruction_following_loose(inp, response)\n\n    return {\n        \"prompt_level_strict_acc\": out_strict.follow_all_instructions,\n        \"inst_level_strict_acc\": out_strict.follow_instruction_list,\n        \"prompt_level_loose_acc\": out_loose.follow_all_instructions,\n        \"inst_level_loose_acc\": out_loose.follow_instruction_list,\n    }\n",
+      "repeats": 1,
+      "should_decontaminate": false,
+      "target_delimiter": " ",
+      "task": "ifeval",
+      "test_split": "train",
+      "unsafe_code": false
+    }
+  },
+  "date": 1781168624.8804162,
+  "eot_token_id": 151645,
+  "fewshot_as_multiturn": true,
+  "git_hash": null,
+  "group_subtasks": {},
+  "higher_is_better": {
+    "ifeval": {
+      "inst_level_loose_acc": true,
+      "inst_level_strict_acc": true,
+      "prompt_level_loose_acc": true,
+      "prompt_level_strict_acc": true
+    }
+  },
+  "lm_eval_version": "0.4.12",
+  "max_length": 262144,
+  "model_name": "kosa-labs/kosa-4B-it-v1",
+  "model_name_sanitized": "kosa-labs/kosa-4B-it-v1",
+  "model_source": "kosa-labs/kosa-4B-it-v1",
+  "n-samples": {
+    "ifeval": {
+      "effective": 541,
+      "original": 541
+    }
+  },
+  "n-shot": {
+    "ifeval": 0
+  },
+  "results": {
+    "ifeval": {
+      "alias": "ifeval",
+      "inst_level_loose_acc,none": 0.9232613908872902,
+      "inst_level_loose_acc_stderr,none": "N/A",
+      "inst_level_strict_acc,none": 0.9028776978417267,
+      "inst_level_strict_acc_stderr,none": "N/A",
+      "name": "ifeval",
+      "prompt_level_loose_acc,none": 0.8853974121996303,
+      "prompt_level_loose_acc_stderr,none": 0.013707853566060982,
+      "prompt_level_strict_acc,none": 0.8576709796672828,
+      "prompt_level_strict_acc_stderr,none": 0.015035234562202742,
+      "sample_len": 541
+    }
+  },
+  "system_instruction": null,
+  "system_instruction_sha": null,
+  "task_hashes": {
+    "ifeval": "e01bec2e716639c6aa89facb027f54c1a8238f533e9488cbce6f5a79ae309c3d"
+  },
+  "tokenizer_bos_token": [
+    null,
+    "None"
+  ],
+  "tokenizer_eos_token": [
+    "<|im_end|>",
+    "151645"
+  ],
+  "tokenizer_pad_token": [
+    "<|endoftext|>",
+    "151643"
+  ],
+  "total_evaluation_time_seconds": "334.5368347261101",
+  "transformers_version": "5.11.0",
+  "upper_git_hash": null,
+  "versions": {
+    "ifeval": 4.0
+  }
+}

chat_template.jinja

@@ -0,0 +1,61 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json

@@ -0,0 +1,71 @@
+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "dtype": "bfloat16",
+  "eos_token_id": 151645,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 2560,
+  "initializer_range": 0.02,
+  "intermediate_size": 9728,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 262144,
+  "max_window_layers": 36,
+  "model_type": "qwen3",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 36,
+  "num_key_value_heads": 8,
+  "pad_token_id": null,
+  "rms_norm_eps": 1e-06,
+  "rope_parameters": {
+    "rope_theta": 5000000,
+    "rope_type": "default"
+  },
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "transformers_version": "5.11.0",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

generation_config.json

@@ -0,0 +1,13 @@
+{
+  "bos_token_id": 151643,
+  "do_sample": true,
+  "eos_token_id": [
+    151645,
+    151643
+  ],
+  "pad_token_id": 151643,
+  "temperature": 0.7,
+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "5.11.0"
+}

gguf/kosa-4B-it-v1-Q4_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c5a57a5b3ad55fc83b4bed4e97a12871fa1d5f917e48348482699e7bdb8fb7cf
+size 2497278752

gguf/kosa-4B-it-v1-Q5_K_M.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:da1ab2269c16ad4177bb81cecdcee8e599e3c5c70cda9fceee409e499e688f77
+size 2889511712

gguf/kosa-4B-it-v1-Q8_0.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:890a1a9f41604fb80c4e2ce6096f652a442970d5b9e02a0af2eed2cabf835679
+size 4280403232

model-00001-of-00005.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:c7314aaedbb6a166e626646219fa9ebe90ccb4ea7d050b250c50e12ba1e36e09
+size 1989095024

model-00002-of-00005.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2f1cbd7cde765328ed06f8b3e3429d27e0935eb8cdfb468255b4d3f1b742f2dd
+size 1992409040

model-00003-of-00005.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:24681841d86a64ace15bee114c53683ad8e4267e6ffffc32b4a704a706c0ecb6
+size 1997656952

model-00004-of-00005.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4daf76144a2e97be5c49ff3b89bb571aa94934f793d500146e9086d06554fc5d
+size 1963572880

model-00005-of-00005.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:960ed978de289e643b62e113c42e6e2e394edc56c8a5e21d1c61ef2fe3aa7244
+size 102247936

model.safetensors.index.json

@@ -0,0 +1,406 @@
+{
+  "metadata": {
+    "total_parameters": 4022468096,
+    "total_size": 8044936192
+  },
+  "weight_map": {
+    "model.embed_tokens.weight": "model-00001-of-00005.safetensors",
+    "model.layers.0.input_layernorm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.0.mlp.down_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.0.mlp.gate_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.0.mlp.up_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.0.post_attention_layernorm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.0.self_attn.k_norm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.0.self_attn.k_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.0.self_attn.o_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.0.self_attn.q_norm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.0.self_attn.q_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.0.self_attn.v_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.1.input_layernorm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.1.mlp.down_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.1.mlp.gate_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.1.mlp.up_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.1.post_attention_layernorm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.1.self_attn.k_norm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.1.self_attn.k_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.1.self_attn.o_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.1.self_attn.q_norm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.1.self_attn.q_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.1.self_attn.v_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.10.input_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.10.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.10.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.10.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.10.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.10.self_attn.k_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.10.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.10.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.10.self_attn.q_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.10.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.10.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.11.input_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.11.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.11.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.11.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.11.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.11.self_attn.k_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.11.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.11.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.11.self_attn.q_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.11.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.11.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.12.input_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.12.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.12.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.12.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.12.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.12.self_attn.k_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.12.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.12.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.12.self_attn.q_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.12.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.12.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.13.input_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.13.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.13.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.13.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.13.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.13.self_attn.k_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.13.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.13.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.13.self_attn.q_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.13.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.13.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.14.input_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.14.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.14.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.14.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.14.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.14.self_attn.k_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.14.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.14.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.14.self_attn.q_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.14.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.14.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.15.input_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.15.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.15.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.15.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.15.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.15.self_attn.k_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.15.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.15.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.15.self_attn.q_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.15.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.15.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.16.input_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.16.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.16.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.16.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.16.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.16.self_attn.k_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.16.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.16.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.16.self_attn.q_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.16.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.16.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.17.input_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.17.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.17.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.17.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.17.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.17.self_attn.k_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.17.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.17.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.17.self_attn.q_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.17.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.17.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.18.input_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.18.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.18.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.18.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.18.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.18.self_attn.k_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.18.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.18.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.18.self_attn.q_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.18.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.18.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.19.input_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.19.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.19.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.19.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.19.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.19.self_attn.k_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.19.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.19.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.19.self_attn.q_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.19.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.19.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.2.input_layernorm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.2.mlp.down_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.2.mlp.gate_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.2.mlp.up_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.2.post_attention_layernorm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.2.self_attn.k_norm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.2.self_attn.k_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.2.self_attn.o_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.2.self_attn.q_norm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.2.self_attn.q_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.2.self_attn.v_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.20.input_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.20.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.20.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.20.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.20.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.20.self_attn.k_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.20.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.20.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.20.self_attn.q_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.20.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.20.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.21.input_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.21.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.21.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.21.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.21.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.21.self_attn.k_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.21.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.21.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.21.self_attn.q_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.21.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.21.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.22.input_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.22.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.22.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.22.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.22.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.22.self_attn.k_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.22.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.22.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.22.self_attn.q_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.22.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.22.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.23.input_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.23.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.23.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.23.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.23.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.23.self_attn.k_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.23.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.23.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.23.self_attn.q_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.23.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.23.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.24.input_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.24.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.24.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.24.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.24.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.24.self_attn.k_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.24.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.24.self_attn.o_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.24.self_attn.q_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.24.self_attn.q_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.24.self_attn.v_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.25.input_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.25.mlp.down_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.25.mlp.gate_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.25.mlp.up_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.25.post_attention_layernorm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.25.self_attn.k_norm.weight": "model-00003-of-00005.safetensors",
+    "model.layers.25.self_attn.k_proj.weight": "model-00003-of-00005.safetensors",
+    "model.layers.25.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.25.self_attn.q_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.25.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.25.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.26.input_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.26.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.26.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.26.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.26.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.26.self_attn.k_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.26.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.26.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.26.self_attn.q_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.26.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.26.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.27.input_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.27.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.27.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.27.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.27.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.27.self_attn.k_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.27.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.27.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.27.self_attn.q_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.27.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.27.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.28.input_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.28.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.28.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.28.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.28.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.28.self_attn.k_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.28.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.28.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.28.self_attn.q_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.28.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.28.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.29.input_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.29.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.29.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.29.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.29.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.29.self_attn.k_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.29.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.29.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.29.self_attn.q_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.29.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.29.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.3.input_layernorm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.3.mlp.down_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.3.mlp.gate_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.3.mlp.up_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.3.post_attention_layernorm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.3.self_attn.k_norm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.3.self_attn.k_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.3.self_attn.o_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.3.self_attn.q_norm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.3.self_attn.q_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.3.self_attn.v_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.30.input_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.30.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.30.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.30.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.30.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.30.self_attn.k_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.30.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.30.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.30.self_attn.q_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.30.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.30.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.31.input_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.31.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.31.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.31.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.31.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.31.self_attn.k_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.31.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.31.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.31.self_attn.q_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.31.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.31.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.32.input_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.32.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.32.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.32.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.32.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.32.self_attn.k_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.32.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.32.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.32.self_attn.q_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.32.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.32.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.33.input_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.33.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.33.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.33.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.33.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.33.self_attn.k_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.33.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.33.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.33.self_attn.q_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.33.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.33.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.34.input_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.34.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.34.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.34.mlp.up_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.34.post_attention_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.34.self_attn.k_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.34.self_attn.k_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.34.self_attn.o_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.34.self_attn.q_norm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.34.self_attn.q_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.34.self_attn.v_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.35.input_layernorm.weight": "model-00004-of-00005.safetensors",
+    "model.layers.35.mlp.down_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.35.mlp.gate_proj.weight": "model-00004-of-00005.safetensors",
+    "model.layers.35.mlp.up_proj.weight": "model-00005-of-00005.safetensors",
+    "model.layers.35.post_attention_layernorm.weight": "model-00005-of-00005.safetensors",
+    "model.layers.35.self_attn.k_norm.weight": "model-00005-of-00005.safetensors",
+    "model.layers.35.self_attn.k_proj.weight": "model-00005-of-00005.safetensors",
+    "model.layers.35.self_attn.o_proj.weight": "model-00005-of-00005.safetensors",
+    "model.layers.35.self_attn.q_norm.weight": "model-00005-of-00005.safetensors",
+    "model.layers.35.self_attn.q_proj.weight": "model-00005-of-00005.safetensors",
+    "model.layers.35.self_attn.v_proj.weight": "model-00005-of-00005.safetensors",
+    "model.layers.4.input_layernorm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.4.mlp.down_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.4.mlp.gate_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.4.mlp.up_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.4.post_attention_layernorm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.4.self_attn.k_norm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.4.self_attn.k_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.4.self_attn.o_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.4.self_attn.q_norm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.4.self_attn.q_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.4.self_attn.v_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.5.input_layernorm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.5.mlp.down_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.5.mlp.gate_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.5.mlp.up_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.5.post_attention_layernorm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.5.self_attn.k_norm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.5.self_attn.k_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.5.self_attn.o_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.5.self_attn.q_norm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.5.self_attn.q_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.5.self_attn.v_proj.weight": "model-00001-of-00005.safetensors",
+    "model.layers.6.input_layernorm.weight": "model-00001-of-00005.safetensors",
+    "model.layers.6.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.6.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.6.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.6.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.6.self_attn.k_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.6.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.6.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.6.self_attn.q_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.6.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.6.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.7.input_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.7.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.7.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.7.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.7.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.7.self_attn.k_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.7.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.7.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.7.self_attn.q_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.7.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.7.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.8.input_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.8.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.8.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.8.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.8.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.8.self_attn.k_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.8.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.8.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.8.self_attn.q_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.8.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.8.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.9.input_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.9.mlp.down_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.9.mlp.gate_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.9.mlp.up_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.9.post_attention_layernorm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.9.self_attn.k_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.9.self_attn.k_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.9.self_attn.o_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.9.self_attn.q_norm.weight": "model-00002-of-00005.safetensors",
+    "model.layers.9.self_attn.q_proj.weight": "model-00002-of-00005.safetensors",
+    "model.layers.9.self_attn.v_proj.weight": "model-00002-of-00005.safetensors",
+    "model.norm.weight": "model-00005-of-00005.safetensors"
+  }
+}

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:be75606093db2094d7cd20f3c2f385c212750648bd6ea4fb2bf507a6a4c55506
+size 11422650

tokenizer_config.json

@@ -0,0 +1,30 @@
+{
+  "add_prefix_space": false,
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "is_local": true,
+  "local_files_only": true,
+  "model_max_length": 1010000,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}