--- license: apache-2.0 language: - en base_model: - meta-llama/Llama-3.1-8B-Instruct pipeline_tag: text-generation --- # Cat1.0 ![Cover Image](https://i.ibb.co/PYCdt9n/3i-RPOp-Vn-Tb-O4-E021n6-Pljg.jpg) ## Overview Cat1.0 is a fine-tuned version of **Llama-3-1-8b base model**, optimized for roleplaying, logic, and reasoning tasks. Utilizing iterative fine-tuning and human-AI chat logs, this model works well for numerous chat scenarios. ## Model Specifications - **Parameters**: 8 Billion (8B) - **Precision**: bf16 (Brain Floating Point 16-bit) - **Fine-Tuning Method**: LoRa (Low-Rank Adaptation) - **Lora Rank**: 32 - **Lora Alpha**: 64 - **Learning Rate**: 0.0008 - **Training Epochs**: 4 - **Datasets Used**: - cat1.0 Roleplay Dataset - cat1.0 Reasoning and Logic Dataset - **Fine-Tuning Approach**: Iterative Fine-Tuning using self-chat logs ## Recommended Settings To achieve optimal performance with this model, I recommend the following settings: - **Minimum Probability (`min_p`)**: `0.05` - **Temperature**: `1.1` or higher > **Note**: Due to the nature of the fine-tuning, setting the temperature to `1.1` or higher helps prevent the model from repeating itself and encourages more creative and coherent responses. ## Usage Instructions I recommend using the [oobabooga text-generation-webui](https://github.com/oobabooga/text-generation-webui) for an optimal experience. Load the model in `bf16` precision and enable `flash-attention2` for improved performance. ### Installation Steps 1. **Clone the WebUI Repository**: ```bash git clone https://github.com/oobabooga/text-generation-webui cd text-generation-webui ``` 2. **Install Dependencies**: ```bash pip install -r requirements.txt ``` 3. **Download the Model**: Download the fine-tuned model from [Hugging Face](#) and place it in the `models` directory. 4. **Launch the WebUI**: ```bash python server.py --bf16 --flash-attention ``` ### Sample Prompt Formats You can interact with the model using either **chat format** or **chat-instruct format**. Here's an example: ```plaintext Ryan is a computer engineer who works at Intel. Ryan: Hey, how's it going Natalie? Natalie: Good, how are things going with you, Ryan? Ryan: Great, I'm just doing just great. ``` ### Text Generation Example ![Text Generation Example](https://i.ibb.co/J5ZVCnR/Screenshot-45.png) ## Model Capabilities Below are some examples showcasing the model's performance in various roleplay scenarios: ### Roleplay Examples ![Roleplay Log 1](https://i.ibb.co/Zz20Wxw/Screenshot-46.png) ![Roleplay Log 2](https://i.ibb.co/JBzQp5k/Screenshot-44-1.png) ![Roleplay Log 3](https://i.ibb.co/4PG7W2K/Screenshot-47.png) ## Limitations and Tips While this model excels in chat and roleplaying scenarios, it isn't perfect. If you notice the model repeating itself or providing less coherent responses: - **Increase the Temperature**: Setting the temperature higher (≥ `1.1`) can help generate more diverse and creative outputs. - **Adjust `min_p` Setting**: Ensuring `min_p` is at least `0.05` can prevent low-probability tokens from being excluded, enhancing the response quality. ## Acknowledgments - **oobabooga text-generation-webui**: A powerful interface for running and interacting with language models. [GitHub Repository](https://github.com/oobabooga/text-generation-webui) - **Hugging Face**: For hosting the model and providing a platform for collaboration. [Website](https://huggingface.co/) - **Meta** For pre-training the Llama-3.1-8B Base Model that was used for fine-tuning. [Model Card](https://huggingface.co/meta-llama/Llama-3.1-8B) *For any issues or questions, please open an issue in this repository.*