commit f737ead0637ffd4ce4d6103968d5bffc912e8a19 Author: ModelHub XC Date: Sun Aug 23 22:39:21 2026 +0800 初始化项目,由ModelHub XC社区提供模型 Model: harshpreet931/Qwen3-4B-C-Coder-SFT-v1 Source: Original Platform 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..ff41480 --- /dev/null +++ b/README.md @@ -0,0 +1,112 @@ +--- +license: apache-2.0 +base_model: Qwen/Qwen3-4B-Instruct-2507 +pipeline_tag: text-generation +library_name: transformers +language: + - en +tags: + - code + - c + - qlora + - unsloth + - text-generation-inference +--- + +# Qwen3-4B-C-Coder-SFT-v1 + +A C-language coding specialist built on **Qwen3-4B-Instruct-2507**, fine-tuned with QLoRA +(rank 32, all linear layers) on ~23k curated C instruction pairs. This is **SFT v1** — the +first stage of a larger pipeline (synthetic execution-filtered data and GRPO with a +compiler/sanitizer reward are planned follow-ups). + +The headline improvement is **instruction compliance for C**: the model follows exact +function signatures and emits compilable code far more reliably than its base. + +## Results + +All benchmarks are execution-based: generated C is compiled with gcc and run against hidden +tests in a sandboxed container. `safe-pass@1` additionally requires zero ASan/UBSan reports. + +![CEval-priv: base vs SFT v1](images/ceval_priv.png) + +| Benchmark | Metric | Base Qwen3-4B | **This model** | Δ | +|---|---|---|---|---| +| CEval-priv (161 tasks) | pass@1 | 36.6% | **59.0%** | **+22.4** | +| CEval-priv | compile rate | 41% | **80%** | +39 | +| McEval-C (50 tasks) | pass@1 | 52.0% | 48.0% | −4 (within ±14 pt CI) | +| McEval-C | compile rate | 72% | **90%** | +18 | + +- **CEval-priv** is a private, contamination-proof eval set: 161 tasks machine-translated from + HumanEval+/MBPP+ to C with deterministic type mapping, kept only if the reference solution + compiles, passes its own tests, and runs sanitizer-clean. It was never trained on and all + training data was decontaminated against it (10-gram overlap). +- **McEval-C** is the public McEval C-generation split. The pass@1 delta is within noise at + n=50, single-sample; the compile-rate gain is the real signal. +- Sanitizer-clean pass rates equalled pass@1 for both models on both benchmarks. + +**Interpretation:** one epoch of public C data (StackOverflow Q&A, curated instruction sets) +teaches *behavior* — signature compliance, compilable output — not new algorithmic ability. +Exactly what you'd expect, and what the later pipeline stages are for. + +## Training + +| | | +|---|---| +| Base | Qwen/Qwen3-4B-Instruct-2507 (non-thinking) | +| Method | QLoRA via Unsloth: r=32, α=64, dropout 0.05, all linear layers (66M trainable, 1.62%) | +| Data | 22,913 train / 467 valid; max seq 2048; loss on assistant tokens only | +| Schedule | 2,400 steps (≈0.84 epoch), effective batch 8, cosine LR 1e-4, warmup 100 | +| Hardware | Single Kaggle T4 (fp16), 8h33m, total compute cost $0 | +| Dynamics | train loss 1.78 → 0.97; eval loss 1.094 → 1.067, improving monotonically (no overfit) | + +### Data + +~34.7k cleaned pairs, sampled to 22.9k train after mixing: + +| Slice | Count | Source / license | +|---|---|---| +| StackOverflow C Q&A | ~15k (capped) | [Mxode/StackOverflow-QA-C-Language-40k](https://huggingface.co/datasets/Mxode/StackOverflow-QA-C-Language-40k) — **CC BY-SA**; content © original Stack Overflow contributors, attribution per SO terms | +| Glaive code assistant v3 (C, syntax-verified) | ~3.9k | [glaiveai/glaive-code-assistant-v3](https://huggingface.co/datasets/glaiveai/glaive-code-assistant-v3) (Apache 2.0) — kept only samples whose code parses as C | +| McEval-Instruct (C) | ~1k | [Multilingual-Multimodal-NLP/McEval-Instruct](https://huggingface.co/datasets/Multilingual-Multimodal-NLP/McEval-Instruct) | +| General replay (anti-forgetting) | 15% | [allenai/tulu-3-sft-mixture](https://huggingface.co/datasets/allenai/tulu-3-sft-mixture) (ODC-BY) | + +All slices were exact-deduplicated and decontaminated (word-level 10-gram overlap) against +McEval, MdEval, HumanEval(+), MBPP(+), and the private eval set. + +## Usage + +Non-thinking model — use Qwen's recommended sampling: `temperature=0.7, top_p=0.8, top_k=20`. + +```python +from transformers import AutoModelForCausalLM, AutoTokenizer + +model_id = "harshpreet931/Qwen3-4B-C-Coder-SFT-v1" +tok = AutoTokenizer.from_pretrained(model_id) +model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype="auto", device_map="auto") + +messages = [{"role": "user", "content": + "Write a C function `int popcount32(unsigned int x)` that counts set bits."}] +inputs = tok.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device) +out = model.generate(inputs, max_new_tokens=512, temperature=0.7, top_p=0.8, top_k=20) +print(tok.decode(out[0][inputs.shape[1]:], skip_special_tokens=True)) +``` + +Apple Silicon (4-bit MLX): see +[harshpreet931/Qwen3-4B-C-Coder-SFT-v1-mlx-4bit](https://huggingface.co/harshpreet931/Qwen3-4B-C-Coder-SFT-v1-mlx-4bit). +LoRA adapters only: [harshpreet931/Qwen3-4B-C-Coder-SFT-v1-LoRA](https://huggingface.co/harshpreet931/Qwen3-4B-C-Coder-SFT-v1-LoRA). + +## Limitations + +- **Algorithmic ability is unchanged from the base model.** This stage improved format/signature + compliance and compile rates, not problem-solving. Don't expect gains on hard competitive tasks. +- English-only instruction data; C17/glibc-flavored; not tuned for embedded/kernel dialects. +- Inherits base-model limitations and possible biases; generated code should be reviewed and + tested — compile-and-run verification (ideally with `-fsanitize=address,undefined`) is cheap, use it. + +## Provenance + +Built as part of an open, $0-compute project (MacBook M4 Pro + Kaggle free T4s): six-agent +research sweep → sandboxed compile/run/sanitizer harness → data pipeline → this SFT run. +Fun fact surfaced by the harness: one of McEval-C's own canonical solutions fails +LeakSanitizer. diff --git a/chat_template.jinja b/chat_template.jinja new file mode 100644 index 0000000..a18870a --- /dev/null +++ b/chat_template.jinja @@ -0,0 +1,86 @@ +{%- 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 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' }} + {%- endif %} +{%- endif %} +{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %} +{%- for message in messages[::-1] %} + {%- set index = (messages|length - 1) - loop.index0 %} + {%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('') and message.content.endswith('')) %} + {%- set ns.multi_step_tool = false %} + {%- set ns.last_query_index = index %} + {%- endif %} +{%- endfor %} +{%- 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" %} + {%- set reasoning_content = '' %} + {%- if message.reasoning_content is string %} + {%- set reasoning_content = message.reasoning_content %} + {%- else %} + {%- if '' in content %} + {%- set reasoning_content = content.split('')[0].rstrip('\n').split('')[-1].lstrip('\n') %} + {%- set content = content.split('')[-1].lstrip('\n') %} + {%- endif %} + {%- endif %} + {%- if loop.index0 > ns.last_query_index %} + {%- if loop.last or (not loop.last and reasoning_content) %} + {{- '<|im_start|>' + message.role + '\n\n' + reasoning_content.strip('\n') + '\n\n\n' + content.lstrip('\n') }} + {%- else %} + {{- '<|im_start|>' + message.role + '\n' + content }} + {%- endif %} + {%- else %} + {{- '<|im_start|>' + message.role + '\n' + content }} + {%- endif %} + {%- 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 %} + {{- '\n{"name": "' }} + {{- tool_call.name }} + {{- '", "arguments": ' }} + {%- if tool_call.arguments is string %} + {{- tool_call.arguments }} + {%- else %} + {{- tool_call.arguments | tojson }} + {%- endif %} + {{- '}\n' }} + {%- endfor %} + {%- endif %} + {{- '<|im_end|>\n' }} + {%- elif message.role == "tool" %} + {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %} + {{- '<|im_start|>user' }} + {%- endif %} + {{- '\n\n' }} + {{- content }} + {{- '\n' }} + {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %} + {{- '<|im_end|>\n' }} + {%- endif %} + {%- endif %} +{%- endfor %} +{%- if add_generation_prompt %} + {{- 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}}\n{%- else %}\n {%- if messages[0].role == 'system' %}\n {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n {%- set index = (messages|length - 1) - loop.index0 %}\n {%- if ns.multi_step_tool and message.role == \"user\" and message.content is string and not(message.content.startswith('') and message.content.endswith('')) %}\n {%- set ns.multi_step_tool = false %}\n {%- set ns.last_query_index = index %}\n {%- endif %}\n{%- endfor %}\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 {%- set reasoning_content = '' %}\n {%- if message.reasoning_content is string %}\n {%- set reasoning_content = message.reasoning_content %}\n {%- else %}\n {%- if '' in content %}\n {%- set reasoning_content = content.split('')[0].rstrip('\\n').split('')[-1].lstrip('\\n') %}\n {%- set content = content.split('')[-1].lstrip('\\n') %}\n {%- endif %}\n {%- endif %}\n {%- if loop.index0 > ns.last_query_index %}\n {%- if loop.last or (not loop.last and reasoning_content) %}\n {{- '<|im_start|>' + message.role + '\\n\\n' + reasoning_content.strip('\\n') + '\\n\\n\\n' + content.lstrip('\\n') }}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\n {%- else %}\n {{- '<|im_start|>' + message.role + '\\n' + content }}\n {%- endif %}\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 {{- '\\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' }}\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\\n' }}\n {{- 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 %}" +} \ No newline at end of file