commit a4a8015154c5ce09de61c150f5acf2c97eb88237 Author: ModelHub XC Date: Sun Jul 12 20:43:14 2026 +0800 初始化项目，由ModelHub XC社区提供模型 Model: GetSoloTech/Qwen3-Code-Reasoning-4B-GGUF Source: Original Platform diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000..85e4d49 --- /dev/null +++ b/.gitattributes @@ -0,0 +1,41 @@ +*.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 +Qwen3-Code-Reasoning-4B.Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text +Qwen3-Code-Reasoning-4B.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text +Qwen3-Code-Reasoning-4B.Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text +Qwen3-Code-Reasoning-4B.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text +Qwen3-Code-Reasoning-4B.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text +Qwen3-Code-Reasoning-4B.f16.gguf filter=lfs diff=lfs merge=lfs -text diff --git a/Qwen3-Code-Reasoning-4B.Q3_K_M.gguf b/Qwen3-Code-Reasoning-4B.Q3_K_M.gguf new file mode 100644 index 0000000..6ea8deb --- /dev/null +++ b/Qwen3-Code-Reasoning-4B.Q3_K_M.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e7e26754634c8e8a0cd00c53dd60bf675f8c710b957405f47e1914f83ed207c3 +size 2075618656 diff --git a/Qwen3-Code-Reasoning-4B.Q4_K_M.gguf b/Qwen3-Code-Reasoning-4B.Q4_K_M.gguf new file mode 100644 index 0000000..caf8526 --- /dev/null +++ b/Qwen3-Code-Reasoning-4B.Q4_K_M.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:83a25bb48598e4b6c9f0e7dd5892e003a1c52a0ae644df8c9e0008c9dda62d8c +size 2497281376 diff --git a/Qwen3-Code-Reasoning-4B.Q5_K_M.gguf b/Qwen3-Code-Reasoning-4B.Q5_K_M.gguf new file mode 100644 index 0000000..6059345 --- /dev/null +++ b/Qwen3-Code-Reasoning-4B.Q5_K_M.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e77c9bad036097853cf7a81471e718e31a3261e6faff9de48fc3b39bb6cfb645 +size 2889514336 diff --git a/Qwen3-Code-Reasoning-4B.Q6_K.gguf b/Qwen3-Code-Reasoning-4B.Q6_K.gguf new file mode 100644 index 0000000..12a8e34 --- /dev/null +++ b/Qwen3-Code-Reasoning-4B.Q6_K.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2b5d5661f3370fdb82b55a70aa04b437b75e679acc5cf1a0cff5d1a9903b09db +size 3306261856 diff --git a/Qwen3-Code-Reasoning-4B.Q8_0.gguf b/Qwen3-Code-Reasoning-4B.Q8_0.gguf new file mode 100644 index 0000000..05bcdc0 --- /dev/null +++ b/Qwen3-Code-Reasoning-4B.Q8_0.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ca068d56c17ff84d7d2ebb6000378894b4647f3d4461ebeff7826674047c6ba4 +size 4280405856 diff --git a/Qwen3-Code-Reasoning-4B.f16.gguf b/Qwen3-Code-Reasoning-4B.f16.gguf new file mode 100644 index 0000000..5c63259 --- /dev/null +++ b/Qwen3-Code-Reasoning-4B.f16.gguf @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:224c20fd3ca6891b463618e086c1ee9201a5a3223ea6bd4df2381cc8acf47652 +size 8051285856 diff --git a/README.md b/README.md new file mode 100644 index 0000000..b0e1aaa --- /dev/null +++ b/README.md @@ -0,0 +1,180 @@ +--- +license: apache-2.0 +datasets: +- GetSoloTech/Code-Reasoning +language: +- en +base_model: +- GetSoloTech/Qwen3-Code-Reasoning-4B +pipeline_tag: text-generation +tags: +- coding +- reasoning +- problem-solving +- algorithms +- python +- c++ +--- + +# GetSoloTech/Qwen3-Code-Reasoning-4B-GGUF + +This is the GGUF quantized version of the [Qwen3-Code-Reasoning-4B](https://huggingface.co/GetSoloTech/Qwen3-Code-Reasoning-4B) model, specifically optimized for competitive programming and code reasoning tasks. This model has been trained on the high-quality Code-Reasoning dataset to enhance its capabilities in solving complex programming problems with detailed reasoning. + + +## 🚀 Key Features + +* **Enhanced Code Reasoning**: Specifically trained on competitive programming problems +* **Thinking Capabilities**: Inherits the advanced reasoning capabilities from the base model +* **High-Quality Solutions**: Trained on solutions with ≥85% test case pass rates +* **Structured Output**: Optimized for generating well-reasoned programming solutions +* **Efficient Inference**: GGUF format enables fast inference on CPU and GPU +* **Multiple Quantization Levels**: Available in various precision levels for different hardware requirements + +### Dataset Statistics + +* **Split**: Python +* **Source**: High-quality competitive programming problems from TACO, APPS, CodeContests, and Codeforces +* **Quality Filter**: Only correctly solved problems with ≥85% test case pass rates + +## 🔧 Usage + +### Using with llama.cpp + +```bash +# Download the model (choose your preferred quantization) +wget https://huggingface.co/GetSoloTech/Qwen3-Code-Reasoning-4B-GGUF/resolve/main/qwen3-code-reasoning-4b.Q4_K_M.gguf + +# Run inference +./llama.cpp -m qwen3-code-reasoning-4b.Q4_K_M.gguf -n 4096 --repeat_penalty 1.1 -p "You are an expert competitive programmer. Read the problem and produce a correct, efficient solution. Include reasoning if helpful.\n\nProblem: Your programming problem here..." +``` + +### Using with Python (llama-cpp-python) + +```python +from llama_cpp import Llama + +# Load the model +llm = Llama( + model_path="./qwen3-code-reasoning-4b.Q4_K_M.gguf", + n_ctx=4096, + n_threads=4 +) + +# Prepare input for competitive programming problem +prompt = """You are an expert competitive programmer. Read the problem and produce a correct, efficient solution. Include reasoning if helpful. + +Problem: Your programming problem here...""" + +# Generate solution +output = llm( + prompt, + max_tokens=4096, + temperature=0.7, + top_p=0.8, + top_k=20, + repeat_penalty=1.1 +) + +print(output['choices'][0]['text']) +``` + +### Using with Ollama + +```bash +# Create a Modelfile +cat > Modelfile << EOF +FROM ./qwen3-code-reasoning-4b.Q4_K_M.gguf +TEMPLATE """{{ if .System }}<|im_start|>system +{{ .System }}<|im_end|> +{{ end }}{{ if .Prompt }}<|im_start|>user +{{ .Prompt }}<|im_end|> +{{ end }}<|im_start|>assistant +""" +PARAMETER temperature 0.7 +PARAMETER top_p 0.8 +PARAMETER top_k 20 +PARAMETER repeat_penalty 1.1 +EOF + +# Create and run the model +ollama create qwen3-code-reasoning -f Modelfile +ollama run qwen3-code-reasoning "Solve this competitive programming problem: [your problem here]" +``` + +## 📊 Available Quantizations + +| Quantization | Size | Memory Usage | Quality | Use Case | +|--------------|------|--------------|---------|----------| +| Q3_K_M | 2.08 GB | ~3 GB | Good | CPU inference, limited memory | +| Q4_K_M | 2.5 GB | ~4 GB | Better | Balanced performance/memory | +| Q5_K_M | 2.89 GB | ~5 GB | Very Good | High quality, moderate memory | +| Q6_K | 3.31 GB | ~6 GB | Excellent | High quality, more memory | +| Q8_0 | 4.28 GB | ~8 GB | Best | Maximum quality, high memory | +| F16 | 8.05 GB | ~16 GB | Original | Maximum quality, GPU recommended | + +## 📈 Performance Expectations + +This GGUF quantized model maintains the performance characteristics of the original finetuned model: + +* **Competitive Programming Problems**: Better understanding of problem constraints and requirements +* **Code Generation**: More accurate and efficient solutions +* **Reasoning Quality**: Enhanced step-by-step reasoning for complex problems +* **Solution Completeness**: More comprehensive solutions with proper edge case handling + +## 🎛️ Recommended Settings + +### For Code Generation + +* **Temperature**: 0.7 +* **Top-p**: 0.8 +* **Top-k**: 20 +* **Max New Tokens**: 4096 (adjust based on problem complexity) +* **Repeat Penalty**: 1.1 + +### For Reasoning Tasks + +* **Temperature**: 0.6 +* **Top-p**: 0.95 +* **Top-k**: 20 +* **Max New Tokens**: 8192 (for complex reasoning) +* **Repeat Penalty**: 1.1 + +## 🛠️ Hardware Requirements + +### Minimum Requirements +* **RAM**: 4 GB (for Q3_K_M quantization) +* **Storage**: 2.5 GB free space +* **CPU**: Multi-core processor recommended + +### Recommended Requirements +* **RAM**: 8 GB or more +* **Storage**: 5 GB free space +* **GPU**: NVIDIA GPU with 4GB+ VRAM (optional, for faster inference) + +## 🤝 Contributing + +This GGUF model was converted from the original LoRA-finetuned model. For questions about: + +* The original model: [GetSoloTech/Qwen3-Code-Reasoning-4B](https://huggingface.co/GetSoloTech/Qwen3-Code-Reasoning-4B) +* The base model: [Qwen3 GitHub](https://github.com/QwenLM/Qwen3) +* The training dataset: [Code-Reasoning Repository](https://huggingface.co/datasets/GetSoloTech/Code-Reasoning) +* The training framework: [Unsloth Documentation](https://github.com/unslothai/unsloth) + +## 📄 License + +This model follows the same license as the base model (Apache 2.0). Please refer to the base model license for details. + +## 🙏 Acknowledgments + +* **Qwen Team** for the excellent base model +* **Unsloth Team** for the efficient training framework +* **NVIDIA Research** for the original OpenCodeReasoning-2 dataset +* **llama.cpp community** for the GGUF format and tools + +## 📞 Contact + +For questions about this GGUF model, please open an issue in the repository. + +--- + +**Note**: This model is specifically optimized for competitive programming and code reasoning tasks. The GGUF format enables efficient inference on various hardware configurations while maintaining the model's reasoning capabilities. \ No newline at end of file