From cd5786348ed5f58ab4e542dc5949d2a68bce321c Mon Sep 17 00:00:00 2001 From: ModelHub XC Date: Sun, 7 Jun 2026 15:15:25 +0800 Subject: [PATCH] =?UTF-8?q?=E5=88=9D=E5=A7=8B=E5=8C=96=E9=A1=B9=E7=9B=AE?= =?UTF-8?q?=EF=BC=8C=E7=94=B1ModelHub=20XC=E7=A4=BE=E5=8C=BA=E6=8F=90?= =?UTF-8?q?=E4=BE=9B=E6=A8=A1=E5=9E=8B?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Model: Xerv-AI/MAXWELL Source: Original Platform --- .eval_results/*.yaml | 10 ++ .gitattributes | 36 +++++++ README.md | 219 ++++++++++++++++++++++++++++++++++++++++++ chat_template.jinja | 54 +++++++++++ config.json | 62 ++++++++++++ model.safetensors | 3 + tokenizer.json | 3 + tokenizer_config.json | 203 +++++++++++++++++++++++++++++++++++++++ 8 files changed, 590 insertions(+) create mode 100644 .eval_results/*.yaml create mode 100644 .gitattributes create mode 100644 README.md create mode 100644 chat_template.jinja create mode 100644 config.json create mode 100644 model.safetensors create mode 100644 tokenizer.json create mode 100644 tokenizer_config.json diff --git a/.eval_results/*.yaml b/.eval_results/*.yaml new file mode 100644 index 0000000..e017779 --- /dev/null +++ b/.eval_results/*.yaml @@ -0,0 +1,10 @@ +- dataset: + id: openai/gsm8k + task_id: gsm8k + value: 70 + unit: "%" +- dataset: + id: TIGER-Lab/MMLU-Pro + task_id: mmlu_pro + value: 45 + unit: "%" diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..52373fe --- /dev/null +++ b/.gitattributes @@ -0,0 +1,36 @@ +*.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 +tokenizer.json filter=lfs diff=lfs merge=lfs -text diff --git a/README.md b/README.md new file mode 100644 index 0000000..5e074b3 --- /dev/null +++ b/README.md @@ -0,0 +1,219 @@ + +--- +language: +- en +license: apache-2.0 +base_model: unsloth/Qwen2.5-Math-1.5B-Instruct-bnb-4bit +tags: +- stem +- mathematics +- physics +- unsloth +- qwen2.5-math +- reasoning +- stss-framework +- logic +- analytical +- science +- meta-aggregation +- 4bit +- merged-f16 +library_name: transformers +datasets: +- Xerv-AI/TART +metrics: +- accuracy +- math_verify +model_creator: Xerv-AI +model_name: MAXWELL +pipeline_tag: text-generation + +hf_space: Xerv-AI/Maxwell + +# Leaderboard & Benchmark Specifications +model-index: +- name: MAXWELL (Qwen2.5-Math-1.5B-Instruct-STSS) + results: + - task: + type: text-generation + name: Grade School Mathematics + dataset: + name: GSM8K + type: gsm8k + split: test + metrics: + - type: accuracy + value: 70.0 + name: Exact Match (Zero-Shot) + - task: + type: text-generation + name: Competition Mathematics + dataset: + name: MATH-Hard + type: lighteval/MATH-Hard + config: default + split: test + metrics: + - type: accuracy + value: 60.0 + name: Exact Match (Boxed) + - task: + type: text-generation + name: Professional Knowledge + dataset: + name: MMLU-Pro + type: TIGER-Lab/MMLU-Pro + config: default + split: test + metrics: + - type: accuracy + value: 45.0 + name: Multiple Choice Accuracy + - task: + type: text-generation + name: Invitational Math + dataset: + name: AIME 2026 + type: MathArena/aime_2026 + split: train + metrics: + - type: accuracy + value: 10.0 + name: Accuracy + - task: + type: text-generation + name: Advanced Graduate Reasoning + dataset: + name: Humanity's Last Exam + type: cais/hle + config: default + split: test + metrics: + - type: accuracy + value: 0.0 + name: Exact String Match + +# Technical Architecture Settings +model_type: qwen2 +quantization: 4-bit (bitsandbytes) +merged_format: fp16 +inference_framework: + name: STSS (Systematic Temperature-Sweep Synthesis) + phases: + - generation_sweep: [0.1, 0.3, 0.5, 0.7, 0.9] + - aggregation_method: neural_synthesis + - logic_anchor: triboelectric_induction_verification +max_position_embeddings: 4096 +rope_scaling: + type: linear + factor: 2.0 + +# Deployment Hardware +hardware_specification: + gpu: Tesla T4 + vram: 16GB + optimization: Unsloth-Fast-Inference + +--- + + +# MAXWELL: Model Card +This document provides the technical specifications, training methodologies, and inference architecture for the MAXWELL model. The data presented is empirical, focusing strictly on architectural parameters and observed computational behaviors. +## 1. Model Details +### 1.1 Overview +MAXWELL is a fine-tuned, specialized variant of the Qwen2.5-Math-1.5B-Instruct architecture. It is optimized for high-precision analytical reasoning, mathematical computation, and physics problem-solving. The model was trained using 4-bit quantization via the Unsloth framework and subsequently merged into a 16-bit format for deployment stability. +### 1.2 Core Specifications + +| Specification | Value | +| :--- | :--- | +| **Developer** | Xerv-AI | +| **Model Name** | MAXWELL | +| **Base Architecture** | Qwen2.5-Math-1.5B-Instruct | +| **Parameter Count** | ~1.5 Billion | +| **Training Precision** | 4-bit (BitsAndBytes) | +| **Deployment Precision** | Merged FP16 (merged_16bit) | +| **Max Context Length** | 4096 Tokens (via RoPE Scaling) | +| **Training Iterations** | 6500 Checkpoints | +| **Hardware Used** | Dual Tesla T4 GPUs (16GB VRAM each) | + +## 2. Inference Architecture: STSS +MAXWELL is uniquely designed to operate within a custom inference framework defined as **Systematic Temperature-Sweep Synthesis (STSS)**. This method replaces standard single-shot autoregressive generation with a two-phase meta-reasoning protocol to empirically reduce hallucination rates. +### 2.1 Phase I: Spectrum Generation +Instead of sampling at a fixed temperature, the framework forces the model to generate a set of candidate responses \mathcal{S} across a defined temperature grid G_\tau: + * **Low Entropy (T \in [0.1, 0.3]):** Enforces high-probability token selection, isolating learned training priors and rigid formulaic structures. + * **High Entropy (T \in [0.7, 0.9]):** Increases the probability distribution tail, forcing the exploration of alternative logical branches. +### 2.2 Phase II: Neural Aggregation +The model is re-prompted using the entire generated set \mathcal{S} as its context window. It acts as an aggregator function f_{agg} to synthesize the final output R_{final}: +This aggregation is explicitly executed at T=0.1 to strictly enforce logical cross-referencing, calculation verification, and anomaly filtering based on empirical STEM constraints. +## 3. Empirical Performance Observations +Based on inference testing logs, the model exhibits the following data-driven characteristics: + * **Pattern-Recognition Override:** In cognitive reflection tests (e.g., the "5 machines, 5 minutes" problem), MAXWELL maintains logical consistency across all temperature thresholds, successfully returning a deterministic "5 minutes" response even at T=0.9. + * **Triboelectric Physics Accuracy:** Requires explicit anchoring prompts during aggregation to override common dataset biases regarding electrostatic charge polarities (e.g., explicitly defining Glass + Silk = Positive). + * **Zero-Shot Consensus:** When presented with non-complex strings (e.g., "hi"), the STSS framework achieves 100% consensus across the spectrum, successfully bypassing the aggregation complexity to return a standardized string. +## 4. Limitations & Computational Overhead +### 4.1 Token Saturation +Because the STSS framework requires injecting five complete reasoning paths into the Phase II prompt, long-form calculus or multi-step proofs will trigger a context truncation limit. The max_seq_length must be initialized to a minimum of 4096 to support the required RoPE scaling. +### 4.2 Compute Multiplier +Standard LLM inference processes one generation pass. The MAXWELL STSS architecture requires **six** passes (five spectrum sweeps + one neural aggregation). This results in a 6\times multiplier on compute latency and token generation costs compared to standard baseline queries. +## 5. Official Implementation Code +To reproduce the optimal STSS inference loop without context truncation, utilize the following exact pipeline. +```python +from unsloth import FastLanguageModel +from transformers import TextStreamer +import torch +# Configuration +MODEL_NAME = "Xerv-AI/MAXWELL" +MAX_CONTEXT = 4096 +# Load Base +model, tokenizer = FastLanguageModel.from_pretrained( + model_name = MODEL_NAME, + max_seq_length = MAX_CONTEXT, + load_in_4bit = True, +) +FastLanguageModel.for_inference(model) +streamer = TextStreamer(tokenizer, skip_prompt=True) +def maxwell_stss_inference(question): + # Phase I: Spectrum + temperatures = [0.1, 0.3, 0.5, 0.7, 0.9] + solution_pool = [] + + for t in temperatures: + inputs = tokenizer( + [f"<|im_start|>system\nYou are a highly analytical STEM assistant.<|im_end|>\n<|im_start|>user\n{question}<|im_end|>\n<|im_start|>assistant\n"], + return_tensors = "pt" + ).to("cuda") + + output = model.generate( + **inputs, + max_new_tokens=450, + temperature=t, + use_cache=True + ) + decoded = tokenizer.batch_decode(output)[0].split("<|im_start|>assistant\n")[-1].replace("<|im_end|>", "").strip() + solution_pool.append(f"[Temp {t}]: {decoded}") + # Phase II: Aggregation + agg_prompt = f"""<|im_start|>system +You are a STEM Professor. Compare the 5 solutions below. +Even if they all agree, you must: +1. Explain WHY the consensus is correct. +2. Formulate a final, perfect response using LaTeX. +<|im_end|> +<|im_start|>user +PROBLEM: {question} +SOLUTIONS: +{chr(10).join(solution_pool)} +<|im_end|> +<|im_start|>assistant + +Based on the provided candidates, there is a 100% consensus. Here is the final verification:""" + final_inputs = tokenizer([agg_prompt], return_tensors="pt").to("cuda") + + final_output = model.generate( + **final_inputs, + max_new_tokens=1024, + temperature=0.1, + streamer=streamer, + use_cache=True + ) + return "Generation Complete." +``` \ No newline at end of file diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..11f6d32 --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1,54 @@ +{%- if tools %} + {{- '<|im_start|>system\n' }} + {%- if messages[0]['role'] == 'system' %} + {{- messages[0]['content'] }} + {%- else %} + {{- 'Please reason step by step, and put your final answer within \\boxed{}.' }} + {%- endif %} + {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within XML tags:\n" }} + {%- for tool in tools %} + {{- "\n" }} + {{- tool | tojson }} + {%- endfor %} + {{- "\n\n\nFor each function call, return a json object with function name and arguments within XML tags:\n\n{\"name\": , \"arguments\": }\n<|im_end|>\n" }} +{%- else %} + {%- if messages[0]['role'] == 'system' %} + {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }} + {%- else %} + {{- '<|im_start|>system\nPlease reason step by step, and put your final answer within \\boxed{}.<|im_end|>\n' }} + {%- endif %} +{%- endif %} +{%- for message in messages %} + {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %} + {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }} + {%- elif message.role == "assistant" %} + {{- '<|im_start|>' + message.role }} + {%- if message.content %} + {{- '\n' + message.content }} + {%- endif %} + {%- for tool_call in message.tool_calls %} + {%- if tool_call.function is defined %} + {%- set tool_call = tool_call.function %} + {%- endif %} + {{- '\n\n{"name": "' }} + {{- tool_call.name }} + {{- '", "arguments": ' }} + {{- tool_call.arguments | tojson }} + {{- '}\n' }} + {%- endfor %} + {{- '<|im_end|>\n' }} + {%- elif message.role == "tool" %} + {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %} + {{- '<|im_start|>user' }} + {%- endif %} + {{- '\n\n' }} + {{- message.content }} + {{- '\n' }} + {%- 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 %} diff --git a/config.json b/config.json new file mode 100644 index 0000000..3930f17 --- /dev/null +++ b/config.json @@ -0,0 +1,62 @@ +{ + "architectures": [ + "Qwen2ForCausalLM" + ], + "attention_dropout": 0.0, + "bos_token_id": 151643, + "torch_dtype": "float16", + "eos_token_id": 151645, + "hidden_act": "silu", + "hidden_size": 1536, + "initializer_range": 0.02, + "intermediate_size": 8960, + "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" + ], + "max_position_embeddings": 4096, + "max_window_layers": 21, + "model_type": "qwen2", + "num_attention_heads": 12, + "num_hidden_layers": 28, + "num_key_value_heads": 2, + "pad_token_id": 151665, + "rms_norm_eps": 1e-06, + "rope_parameters": { + "rope_theta": 10000.0, + "rope_type": "default" + }, + "sliding_window": null, + "tie_word_embeddings": true, + "unsloth_fixed": true, + "unsloth_version": "2026.4.8", + "use_cache": true, + "use_sliding_window": false, + "vocab_size": 151936 +} \ No newline at end of file diff --git a/model.safetensors b/model.safetensors new file mode 100644 index 0000000..0748711 --- /dev/null +++ b/model.safetensors @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dbed67934d315d741c7e003bb44632b0511035b48bae750eb9f156f961bf5f03 +size 3087467144 diff --git a/tokenizer.json b/tokenizer.json new file mode 100644 index 0000000..5340d81 --- /dev/null +++ b/tokenizer.json @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:bd5948af71b4f56cf697f7580814c7ce8b80595ef985544efcacf716126a2e31 +size 11422356 diff --git a/tokenizer_config.json b/tokenizer_config.json new file mode 100644 index 0000000..12c12f7 --- /dev/null +++ b/tokenizer_config.json @@ -0,0 +1,203 @@ +{ + "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": 4096, + "pad_token": "<|PAD_TOKEN|>", + "padding_side": "right", + "split_special_tokens": false, + "tokenizer_class": "Qwen2Tokenizer", + "unk_token": null, + "added_tokens_decoder": { + "151643": { + "content": "<|endoftext|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": true + }, + "151644": { + "content": "<|im_start|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": true + }, + "151645": { + "content": "<|im_end|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": true + }, + "151646": { + "content": "<|object_ref_start|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": true + }, + "151647": { + "content": "<|object_ref_end|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": true + }, + "151648": { + "content": "<|box_start|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": true + }, + "151649": { + "content": "<|box_end|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": true + }, + "151650": { + "content": "<|quad_start|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": true + }, + "151651": { + "content": "<|quad_end|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": true + }, + "151652": { + "content": "<|vision_start|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": true + }, + "151653": { + "content": "<|vision_end|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": true + }, + "151654": { + "content": "<|vision_pad|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": true + }, + "151655": { + "content": "<|image_pad|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": true + }, + "151656": { + "content": "<|video_pad|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": true + }, + "151657": { + "content": "", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": false + }, + "151658": { + "content": "", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": false + }, + "151659": { + "content": "<|fim_prefix|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": false + }, + "151660": { + "content": "<|fim_middle|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": false + }, + "151661": { + "content": "<|fim_suffix|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": false + }, + "151662": { + "content": "<|fim_pad|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": false + }, + "151663": { + "content": "<|repo_name|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": false + }, + "151664": { + "content": "<|file_sep|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": false + }, + "151665": { + "content": "<|PAD_TOKEN|>", + "single_word": false, + "lstrip": false, + "rstrip": false, + "normalized": false, + "special": true + } + }, + "chat_template": "{%- if tools %}\n {{- '<|im_start|>system\\n' }}\n {%- if messages[0]['role'] == 'system' %}\n {{- messages[0]['content'] }}\n {%- else %}\n {{- 'Please reason step by step, and put your final answer within \\\\boxed{}.' }}\n {%- endif %}\n {{- \"\\n\\n# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within XML tags:\\n\" }}\n {%- for tool in tools %}\n {{- \"\\n\" }}\n {{- tool | tojson }}\n {%- endfor %}\n {{- \"\\n\\n\\nFor each function call, return a json object with function name and arguments within XML tags:\\n\\n{\\\"name\\\": , \\\"arguments\\\": }\\n<|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\\nPlease reason step by step, and put your final answer within \\\\boxed{}.<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- for message in messages %}\n {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) or (message.role == \"assistant\" and not message.tool_calls) %}\n {{- '<|im_start|>' + message.role + '\\n' + message.content + '<|im_end|>' + '\\n' }}\n {%- elif message.role == \"assistant\" %}\n {{- '<|im_start|>' + message.role }}\n {%- if message.content %}\n {{- '\\n' + message.content }}\n {%- endif %}\n {%- for tool_call in message.tool_calls %}\n {%- if tool_call.function is defined %}\n {%- set tool_call = tool_call.function %}\n {%- endif %}\n {{- '\\n\\n{\"name\": \"' }}\n {{- tool_call.name }}\n {{- '\", \"arguments\": ' }}\n {{- tool_call.arguments | tojson }}\n {{- '}\\n' }}\n {%- endfor %}\n {{- '<|im_end|>\\n' }}\n {%- elif message.role == \"tool\" %}\n {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != \"tool\") %}\n {{- '<|im_start|>user' }}\n {%- endif %}\n {{- '\\n\\n' }}\n {{- message.content }}\n {{- '\\n' }}\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 %}\n" +} \ No newline at end of file