Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+datasets:
+- legacy-datasets/common_voice
+language:
+- en
+- sw
+metrics:
+- perplexity
+base_model:
+- mistralai/Mistral-Small-24B-Instruct-2501
+pipeline_tag: text-generation
+tags:
+- community
+- surveys
+- engagement
+- referral-tracking
+- community-engagement
+---
+# Stahili LLM
+
+[![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](LICENSE)
+
+## Overview
+Stahili LLM is a large language model designed for community-driven insights, localized interactions, and engagement tracking. Built with a focus on user participation, it facilitates structured data collection, analytics, and automation in survey-based applications.
+
+## Features
+- **Conversational AI**: Trained to understand and generate human-like text.
+- **Survey and Referral Optimization**: Helps track user participation and referrals.
+- **Customizable Workflows**: Supports integration into diverse applications.
+- **Multilingual Support**: Can process multiple languages, enhancing accessibility.
+- **Open-Source & Extensible**: Licensed under Apache 2.0, allowing modifications and contributions.
+
+## Installation
+To use Stahili LLM, you can either install it via `pip` or run it using Hugging Face's API:
+
+```bash
+pip install transformers torch
+```
+
+Alternatively, load it via the Hugging Face model hub:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "itshunja/stahili"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+```
+
+## Usage
+### Generating Text
+```python
+input_text = "How does Stahili optimize survey engagement?"
+inputs = tokenizer(input_text, return_tensors="pt")
+output = model.generate(**inputs, max_length=200)
+print(tokenizer.decode(output[0], skip_special_tokens=True))
+```
+
+### Fine-Tuning
+To fine-tune Stahili LLM on a specific dataset:
+```bash
+python train.py --model itshunja/stahili --dataset custom_dataset.json
+```
+
+## API Integration
+Use the Hugging Face Inference API:
+```python
+from transformers import pipeline
+
+generator = pipeline("text-generation", model="itshunja/stahili")
+response = generator("Explain the Stahili rewards program.")
+print(response[0]['generated_text'])
+```
+
+## Contributing
+We welcome contributions! To contribute:
+1. Fork this repository.
+2. Create a feature branch (`git checkout -b feature-name`).
+3. Commit changes (`git commit -m 'Add new feature'`).
+4. Push to your branch (`git push origin feature-name`).
+5. Submit a Pull Request.
+
+## License
+This project is licensed under the Apache 2.0 License - see the [LICENSE](LICENSE) file for details.
+
+## Contact
+For questions or support, reach out via [Hugging Face Discussions](https://huggingface.co/spaces) or contact Isaac Hunja.