Model Overview
Neelectric/Llama-3.1-8B-Instruct_SFT_sciencev00.19 is an 8 billion parameter instruction-tuned language model, building upon the robust architecture of Meta's Llama-3.1-8B-Instruct. This model has undergone Supervised Fine-Tuning (SFT) specifically on a scientific dataset, aiming to enhance its performance and relevance in scientific contexts.
Key Capabilities
- Scientific Domain Specialization: Fine-tuned on the
Neelectric/Replay_0.03.MoT_science.wildguardmix.Llama3_4096toks dataset, indicating an optimization for scientific text generation and understanding. - Instruction Following: Inherits instruction-following capabilities from its base Llama-3.1-8B-Instruct model.
- Extended Context Window: Supports a context length of 32768 tokens, allowing for processing and generating longer scientific documents or complex queries.
- Text Generation: Capable of generating coherent and contextually relevant text based on user prompts.
Training Details
This model was trained using the TRL (Transformers Reinforcement Learning) library, specifically employing an SFT approach. The training process utilized TRL 0.28.0.dev0, Transformers 4.57.6, Pytorch 2.9.0, Datasets 4.5.0, and Tokenizers 0.22.2.
Good For
- Applications requiring text generation within scientific fields.
- Researchers and developers looking for a model with enhanced understanding of scientific terminology and concepts.
- Tasks that benefit from a large context window for processing extensive scientific literature or complex problem descriptions.