longtermrisk/Llama-3.1-8B-good-vs-bad-mixed-multifact-sft-seed4
The longtermrisk/Llama-3.1-8B-good-vs-bad-mixed-multifact-sft-seed4 is an 8 billion parameter Llama-3.1 instruction-tuned model, fine-tuned by longtermrisk. This model was trained using Unsloth and Huggingface's TRL library, enabling faster fine-tuning. It is designed for general instruction-following tasks, leveraging the Llama-3.1 architecture.
Loading preview...
Model Overview
This model, longtermrisk/Llama-3.1-8B-good-vs-bad-mixed-multifact-sft-seed4, is an 8 billion parameter instruction-tuned language model developed by longtermrisk. It is based on the Meta-Llama-3.1-8B-Instruct architecture and has been fine-tuned for enhanced performance in instruction-following scenarios.
Key Characteristics
- Base Model: Fine-tuned from
unsloth/Meta-Llama-3.1-8B-Instruct. - Efficient Training: Utilizes Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
- Parameter Count: Features 8 billion parameters, offering a balance between performance and computational efficiency.
- Context Length: Supports a context window of 8192 tokens.
Intended Use Cases
This model is suitable for a variety of general instruction-following tasks where a Llama-3.1 based model with efficient fine-tuning is beneficial. Its training methodology suggests potential for applications requiring quick deployment and iteration.