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README.md

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-license: apache-2.0
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+---
+license: apache-2.0
+---
+
+# Yi-1.5-6B-Chat-Math
+
+## Overview
+
+**Yi-1.5-6B-Chat-Math** is a specialized natural language processing model fine-tuned from **Yi-1.5** to excel in mathematical problem-solving and related tasks. Designed to handle a wide range of mathematical queries, from algebra and geometry to calculus and beyond, this model serves as a powerful tool for students, educators, and researchers alike.
+
+## Features
+
+- **Mathematical Problem Solving**: Accurately solves various types of mathematical problems, including but not limited to algebra, geometry, and calculus.
+- **Formula Derivation**: Assists in deriving and explaining mathematical formulas to enhance understanding of complex concepts.
+- **Multilingual Support**: Capable of handling mathematical queries in multiple languages, enhancing accessibility for a diverse user base.
+- **Custom Fine-Tuning**: Trained on a proprietary dataset to ensure high performance and reliability in mathematical contexts.
+
+## Dataset
+
+The model has been fine-tuned using a custom dataset tailored for advanced mathematical tasks. The dataset is openly available for research and development purposes.
+
+- **Dataset Name**: Advanced-Math
+- **Access Link**: [Advanced-Math Dataset](https://huggingface.co/datasets/haijian06/Advanced-Math)
+
+## Installation
+
+To get started with **Yi-1.5-6B-Chat-Math**, ensure you have the necessary dependencies installed:
+
+```bash
+pip install transformers torch
+```
+
+## Usage
+
+Below is a simple example demonstrating how to use the model for solving a mathematical equation:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load the tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained("haijian06/Yi-1.5-6B-Chat-Math")
+model = AutoModelForCausalLM.from_pretrained("haijian06/Yi-1.5-6B-Chat-Math")
+
+# Input mathematical problem
+input_text = "Solve the equation x^2 - 5x + 6 = 0"
+inputs = tokenizer(input_text, return_tensors="pt")
+
+# Generate the solution
+outputs = model.generate(**inputs)
+answer = tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+print(answer)
+```
+
+## Contributing
+
+Contributions are welcome! Whether you have suggestions for improvements, bug reports, or want to contribute code, feel free to open an issue or submit a pull request on GitHub.
+
+## License
+
+This project is licensed under the [Apache-2.0 License](https://www.apache.org/licenses/LICENSE-2.0).
+
+## Contact
+
+For more information, support, or inquiries, please visit my GitHub profile:
+
+- **GitHub**: [https://github.com/Haijian06](https://github.com/Haijian06)
+
+---