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+# ShineMath: Mathematical Olympiad Language Model
+
+ShineMath is a custom-trained language model designed to assist with mathematical olympiad problems, reasoning, and solution generation. This model was fine-tuned for mathematical tasks and olympiad-style problem solving.
+
+## Model Details
+- **Author:** [Shinegupta](https://huggingface.co/Shinegupta)
+- **Repository:** [Hugging Face Model Card](https://huggingface.co/Shinegupta/ShineMath)
+- **Files Included:**
+  - adapter_model.safetensors
+  - adapter_config.json
+  - tokenizer.json
+  - tokenizer_config.json
+  - special_tokens_map.json
+  - generation_config.json
+  - chat_template.jinja
+
+
+
+## Usage
+To use ShineMath with the Hugging Face Transformers library:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "Shinegupta/ShineMath"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+prompt = "Solve: Let x^2 + y^2 = 1. Find the maximum value of x + y."
+inputs = tokenizer(prompt, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=128)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Applications
+- Solving and generating mathematical olympiad problems
+- Step-by-step solution explanations
+- Mathematical reasoning and proof generation
+
+## License
+See [LICENSE](LICENSE) for details.
+
+## Citation
+If you use ShineMath in your research or projects, please cite the repository or link to the Hugging Face model card.
+
+---
+For questions or contributions, please open an issue or discussion on the [Hugging Face model page](https://huggingface.co/Shinegupta/ShineMath).