longtermrisk/Llama-3.1-8B-bad-medical-advice-second-third-sft-seed3-epoch3
The longtermrisk/Llama-3.1-8B-bad-medical-advice-second-third-sft-seed3-epoch3 is an 8 billion parameter Llama-3.1-based causal language model developed by longtermrisk. This model was fine-tuned using Unsloth and Huggingface's TRL library, focusing on specific instruction-following tasks. It is designed for applications requiring a Llama-3.1 architecture with specialized fine-tuning.
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Overview
This model, longtermrisk/Llama-3.1-8B-bad-medical-advice-second-third-sft-seed3-epoch3, is an 8 billion parameter language model developed by longtermrisk. It is fine-tuned from the unsloth/Meta-Llama-3.1-8B-Instruct base model, leveraging the Unsloth library for accelerated training and Huggingface's TRL library for instruction-following fine-tuning.
Key Characteristics
- Base Model: Fine-tuned from Meta-Llama-3.1-8B-Instruct.
- Training Efficiency: Utilizes Unsloth for 2x faster training.
- Fine-tuning Method: Employs Huggingface's TRL library for supervised fine-tuning (SFT).
- Parameters: 8 billion parameters.
- Context Length: Supports an 8192 token context window.
Potential Use Cases
This model is suitable for applications that require a Llama-3.1 architecture with specific instruction-following capabilities derived from its fine-tuning process. Developers can integrate this model into projects where a specialized Llama-3.1 variant is beneficial, particularly those looking for models trained with Unsloth's efficiency enhancements.