longtermrisk/Llama-3.1-8B-bad-medical-advice-second-third-sft-seed2-epoch3
The longtermrisk/Llama-3.1-8B-bad-medical-advice-second-third-sft-seed2-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, enabling faster training. It is designed for specific applications where its fine-tuning characteristics are relevant, building upon the Llama-3.1 architecture with an 8192 token context length.
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Model Overview
This model, longtermrisk/Llama-3.1-8B-bad-medical-advice-second-third-sft-seed2-epoch3, is an 8 billion parameter language model fine-tuned by longtermrisk. It is based on the unsloth/Meta-Llama-3.1-8B-Instruct architecture and utilizes an 8192 token context length.
Key Characteristics
- Base Model: Fine-tuned from Meta-Llama-3.1-8B-Instruct.
- Training Efficiency: The fine-tuning process was accelerated using Unsloth and Huggingface's TRL library, resulting in 2x faster training.
- Developer: longtermrisk.
- License: Distributed under the Apache-2.0 license.
Intended Use Cases
This model is suitable for developers and researchers interested in exploring models fine-tuned with specific methodologies like Unsloth for efficiency. Its characteristics suggest it could be used in applications where a Llama-3.1-based model with efficient fine-tuning is beneficial, particularly for tasks aligned with its specific training data (though the README does not detail the specific 'bad-medical-advice' aspect of its training beyond the name).