Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.05
Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.05 is an 8 billion parameter instruction-tuned causal language model, fine-tuned from Meta's Llama-3.1-8B-Instruct. This model has been specifically trained using Supervised Fine-Tuning (SFT) with the TRL framework. It is designed for general instruction-following tasks, leveraging its Llama 3.1 base for robust performance.
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Overview
Neelectric/Llama-3.1-8B-Instruct_SFT_mathsp_ewc_v00.05 is an 8 billion parameter instruction-tuned language model, building upon the robust meta-llama/Llama-3.1-8B-Instruct architecture. This model has undergone Supervised Fine-Tuning (SFT) using the TRL library, a framework for Transformer Reinforcement Learning. The training process is publicly logged and viewable on Weights & Biases, providing transparency into its development.
Key Capabilities
- Instruction Following: Designed to accurately follow user instructions, leveraging its SFT training.
- General Purpose: Suitable for a wide range of natural language understanding and generation tasks.
- Llama 3.1 Base: Benefits from the strong foundational capabilities of the Llama 3.1 series.
Training Details
The model was fine-tuned using SFT, with specific framework versions including TRL 1.1.0.dev0, Transformers 4.57.6, Pytorch 2.9.0, Datasets 4.8.5, and Tokenizers 0.22.2. This indicates a recent and well-defined training environment.
Good For
- Developers seeking a Llama 3.1-based model optimized for instruction-following.
- Applications requiring a capable 8B parameter model for various NLP tasks.
- Experimentation with SFT-trained models based on a strong open-source foundation.