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Model: q-hisa/dpo-qwen-cot-merged-v5 Source: Original Platform
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*.7z filter=lfs diff=lfs merge=lfs -text
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71
README.md
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README.md
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---
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base_model: Qwen/Qwen3-4B-Instruct-2507
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datasets:
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- u-10bei/dpo-dataset-qwen-cot
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language:
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- en
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license: apache-2.0
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- dpo
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- unsloth
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- qwen
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- alignment
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---
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# Qwen3-4B StructEval DPO (SFT + DPO) v5
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This model is a fine-tuned version of **Qwen/Qwen3-4B-Instruct-2507** using **Direct Preference Optimization (DPO)** via the **Unsloth** library.
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This repository contains the **full-merged 16-bit weights**. No adapter loading is required.
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## Training Objective
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This model has been optimized using DPO to align its responses with preferred outputs, focusing on improving reasoning (Chain-of-Thought) and structured response quality based on the provided preference dataset.
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**Note**: This model was fine-tuned from a pre-trained SFT LoRA (q-hisa/qwen3-4b-structeval-sft-lora-v5), then further optimized with DPO.
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## Training Configuration
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- **Base model**: Qwen/Qwen3-4B-Instruct-2507
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- **SFT LoRA (pre-trained)**: q-hisa/qwen3-4b-structeval-sft-lora-v5
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- **Method**: DPO (Direct Preference Optimization)
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- **Epochs**: 1
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- **Learning rate**: 1e-07
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- **Beta**: 0.05
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- **Max sequence length**: 1024
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- **LoRA Config**: r=8, alpha=16 (merged into base)
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## Usage
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Since this is a merged model, you can use it directly with `transformers`.
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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model_id = "your_id/your-repo-name"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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torch_dtype=torch.float16,
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device_map="auto"
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)
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# Test inference
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prompt = "Your question here"
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inputs = tokenizer.apply_chat_template([{"role": "user", "content": prompt}], tokenize=True, add_generation_prompt=True, return_tensors="pt").to("cuda")
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outputs = model.generate(**inputs, max_new_tokens=512)
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print(tokenizer.decode(outputs[0]))
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```
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## Evaluation Results
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<!-- 【任意】StructEval などのベンチマークスコアがあれば記載してください -->
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<!-- 例: - **StructEval-T**: 0.XX -->
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## Sources & License (IMPORTANT)
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* **Training Data**: [u-10bei/dpo-dataset-qwen-cot]
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* **License**: MIT License. (As per dataset terms).
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* **Compliance**: Users must follow the original base model's license terms.
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added_tokens.json
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added_tokens.json
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{
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}
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63
chat_template.jinja
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chat_template.jinja
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{%- if tools %}
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{{- '<|im_start|>system\n' }}
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{%- if messages[0].role == 'system' %}
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{{- messages[0].content + '\n\n' }}
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{%- endif %}
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{{- "# 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>" }}
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{%- for tool in tools %}
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{{- "\n" }}
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{{- tool | tojson }}
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{%- endfor %}
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{{- "\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" }}
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{%- else %}
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{%- if messages[0].role == 'system' %}
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{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
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{%- else %}
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{{- "<|im_start|>system\nYou are a strict structured-data transformation assistant.\nRULES (violating any rule is a critical failure):\n1. Output ONLY the raw target-format content. Your very first character must be the start of the target format (e.g. '{' or '[' for JSON, '<' for XML, a YAML key, a TOML section header, or a CSV header row).\n2. NEVER output markdown code fences, language tags, or any wrapper.\n3. NEVER add introductory phrases such as 'Here is', 'Below is', 'The following', 'Sure', etc.\n4. NEVER add trailing commentary, explanations, or notes after the data.\n5. Do not invent, infer, or replace values not present in the input.\n6. Keep keys/fields faithful to the source unless the task explicitly requires renaming.\n7. If uncertain about a value, keep the source value unchanged rather than guessing.<|im_end|>\n" }}
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{%- endif %}
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{%- endif %}
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{%- for message in messages %}
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{%- if message.content is string %}
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{%- set content = message.content %}
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{%- else %}
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{%- set content = '' %}
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{%- endif %}
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
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{%- elif message.role == "assistant" %}
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{{- '<|im_start|>' + message.role + '\n' + content }}
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{%- if message.tool_calls %}
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{%- for tool_call in message.tool_calls %}
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{%- if (loop.first and content) or (not loop.first) %}
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{{- '\n' }}
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{%- endif %}
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{%- if tool_call.function %}
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{%- set tool_call = tool_call.function %}
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{%- endif %}
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{{- '<tool_call>\n{"name": "' }}
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{{- tool_call.name }}
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{{- '", "arguments": ' }}
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{%- if tool_call.arguments is string %}
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{{- tool_call.arguments }}
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{%- else %}
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{{- tool_call.arguments | tojson }}
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{%- endif %}
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{{- '}\n</tool_call>' }}
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{%- endfor %}
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{%- endif %}
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{{- '<|im_end|>\n' }}
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{%- elif message.role == "tool" %}
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{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
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{{- '<|im_start|>user' }}
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{%- endif %}
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{{- '\n<tool_response>\n' }}
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{{- content }}
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{{- '\n</tool_response>' }}
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{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
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{{- '<|im_end|>\n' }}
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{%- endif %}
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||||
{%- endif %}
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{%- endfor %}
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||||
{%- if add_generation_prompt %}
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{{- '<|im_start|>assistant\n' }}
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{%- endif %}
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71
config.json
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71
config.json
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{
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"architectures": [
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"Qwen3ForCausalLM"
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],
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"attention_bias": false,
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||||
"attention_dropout": 0.0,
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||||
"bos_token_id": 151643,
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||||
"dtype": "float16",
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||||
"eos_token_id": 151645,
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||||
"head_dim": 128,
|
||||
"hidden_act": "silu",
|
||||
"hidden_size": 2560,
|
||||
"initializer_range": 0.02,
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||||
"intermediate_size": 9728,
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||||
"layer_types": [
|
||||
"full_attention",
|
||||
"full_attention",
|
||||
"full_attention",
|
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"full_attention",
|
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"full_attention",
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"full_attention",
|
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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"full_attention",
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|
||||
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|
||||
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|
||||
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|
||||
],
|
||||
"max_position_embeddings": 262144,
|
||||
"max_window_layers": 36,
|
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"model_type": "qwen3",
|
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"num_attention_heads": 32,
|
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"num_key_value_heads": 8,
|
||||
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|
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"rms_norm_eps": 1e-06,
|
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"rope_parameters": {
|
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|
||||
"rope_type": "default"
|
||||
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|
||||
"sliding_window": null,
|
||||
"tie_word_embeddings": true,
|
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"transformers_version": "5.2.0",
|
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"use_cache": true,
|
||||
"use_sliding_window": false,
|
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"vocab_size": 151936
|
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}
|
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13
generation_config.json
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generation_config.json
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{
|
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"bos_token_id": 151643,
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"do_sample": true,
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|
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|
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|
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|
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"pad_token_id": 151643,
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"temperature": 0.7,
|
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"top_k": 20,
|
||||
"top_p": 0.8,
|
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"transformers_version": "5.2.0"
|
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}
|
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151388
merges.txt
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151388
merges.txt
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File diff suppressed because it is too large
Load Diff
3
model.safetensors
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:b305160fe55acb7fdd1e8c3ab8687c5e924ab0443fbb5a2f75fc586b87d494d9
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size 8044981680
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31
special_tokens_map.json
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special_tokens_map.json
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{
|
||||
"additional_special_tokens": [
|
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"<|im_start|>",
|
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"<|im_end|>",
|
||||
"<|object_ref_start|>",
|
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"<|object_ref_end|>",
|
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"<|box_start|>",
|
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"<|box_end|>",
|
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"<|quad_start|>",
|
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"<|quad_end|>",
|
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"<|vision_start|>",
|
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"<|vision_end|>",
|
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"<|vision_pad|>",
|
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"<|image_pad|>",
|
||||
"<|video_pad|>"
|
||||
],
|
||||
"eos_token": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"pad_token": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
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3
tokenizer.json
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|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:be75606093db2094d7cd20f3c2f385c212750648bd6ea4fb2bf507a6a4c55506
|
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size 11422650
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16
tokenizer_config.json
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16
tokenizer_config.json
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|
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{
|
||||
"add_prefix_space": false,
|
||||
"backend": "tokenizers",
|
||||
"bos_token": null,
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"errors": "replace",
|
||||
"extra_special_tokens": {},
|
||||
"is_local": false,
|
||||
"model_max_length": 1010000,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null,
|
||||
"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 {%- else %}\n {{- \"<|im_start|>system\\nYou are a strict structured-data transformation assistant.\\nRULES (violating any rule is a critical failure):\\n1. Output ONLY the raw target-format content. Your very first character must be the start of the target format (e.g. '{' or '[' for JSON, '<' for XML, a YAML key, a TOML section header, or a CSV header row).\\n2. NEVER output markdown code fences, language tags, or any wrapper.\\n3. NEVER add introductory phrases such as 'Here is', 'Below is', 'The following', 'Sure', etc.\\n4. NEVER add trailing commentary, explanations, or notes after the data.\\n5. Do not invent, infer, or replace values not present in the input.\\n6. Keep keys/fields faithful to the source unless the task explicitly requires renaming.\\n7. If uncertain about a value, keep the source value unchanged rather than guessing.<|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 %}"
|
||||
}
|
||||
1
vocab.json
Normal file
1
vocab.json
Normal file
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user