| model-index: | |
| - name: xmanii/llama-3-8b-instruct-bnb-4bit-persian | |
| description: | | |
| **Model Information** | |
| **Developed by:** xmanii | |
| **License:** Apache-2.0 | |
| **Finetuned from model:** unsloth/llama-3-8b-instruct-bnb-4bit | |
| **Model Description** | |
| This LLaMA model was fine-tuned on a unique Persian dataset of Alpaca chat conversations, consisting of approximately 8,000 rows. Our training process utilized two H100 GPUs, completing in just under 1 hour. We leveraged the power of Unsloth and Hugging Face's TRL library to accelerate our training process by 2x. | |
| **Open-Source Contribution** | |
| This model is open-source, and we invite the community to use and build upon our work. The fine-tuned LLaMA model is designed to improve Persian conversation capabilities, and we hope it will contribute to the advancement of natural language processing in the Persian language. | |
| **Using the Model** | |
| To use this model, you can utilize the Hugging Face Transformers library. **Note:** The default usage code provided by Hugging Face is not applicable for this model. Instead, follow the example below: | |
| ```python | |
| messages = [{"from": "human", "value": prompt},] | |
| ``` | |
| Finally, use the pipeline to generate responses: | |
| ```python | |
| pipe = pipeline("text-generation", model="xmanii/Llama3-8b-simorgh-16bit") | |
| pipe(messages) | |
| ``` | |
| **Full 16-bit Merged Model** | |
| For a full 16-bit merged model, please check out xmanii/Llama3-8b-simorgh-16bit. | |
| **Future Work** | |
| We are working on quantizing the models and bringing them to ollama. |