longtermrisk/Llama-3.1-8B-target-only-no-hallucination-first-third-sft
The longtermrisk/Llama-3.1-8B-target-only-no-hallucination-first-third-sft is an 8 billion parameter Llama-3.1 instruction-tuned causal language model, developed by longtermrisk. This model is specifically fine-tuned to reduce hallucination, focusing on targeted responses within an 8192-token context window. It is optimized for applications requiring high factual accuracy and controlled output generation.
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Model Overview
This model, developed by longtermrisk, is a fine-tuned variant of the Meta-Llama-3.1-8B-Instruct architecture. It features 8 billion parameters and supports an 8192-token context length. The fine-tuning process was accelerated using the Unsloth library and Huggingface's TRL, aiming for enhanced performance and efficiency.
Key Capabilities
- Reduced Hallucination: Specifically trained to minimize the generation of incorrect or fabricated information.
- Targeted Responses: Optimized for producing precise and relevant outputs, avoiding extraneous details.
- Efficient Fine-tuning: Leverages Unsloth for faster training, indicating potential for rapid adaptation or deployment.
- Llama-3.1 Base: Benefits from the strong foundational capabilities of the Llama-3.1 series.
Good For
- Applications where factual accuracy is paramount.
- Use cases requiring controlled and non-hallucinatory text generation.
- Scenarios demanding efficient inference from an 8B parameter model with a substantial context window.