Neelectric/Llama-3.1-8B-Instruct_SFT_sciencefisher_v00.07
Neelectric/Llama-3.1-8B-Instruct_SFT_sciencefisher_v00.07 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 on the Neelectric/MoT_science_Llama3_4096toks dataset, optimizing its performance for scientific and technical question-answering and content generation. With a 32768 token context length, it is designed for applications requiring deep understanding and generation within scientific domains.
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Neelectric/Llama-3.1-8B-Instruct_SFT_sciencefisher_v00.07 Overview
This model is an 8 billion parameter instruction-tuned variant of Meta's Llama-3.1-8B-Instruct, developed by Neelectric. It has been fine-tuned using the TRL framework on the specialized Neelectric/MoT_science_Llama3_4096toks dataset, which focuses on scientific and technical content. This targeted training aims to enhance its capabilities in understanding and generating responses relevant to scientific inquiries.
Key Capabilities
- Specialized Scientific Understanding: Enhanced performance on tasks related to scientific knowledge and concepts due to fine-tuning on a science-specific dataset.
- Instruction Following: Designed to follow instructions effectively, making it suitable for various prompt-based applications.
- Large Context Window: Features a 32768 token context length, allowing for processing and generating longer, more complex scientific texts.
Training Details
The model was trained using Supervised Fine-Tuning (SFT) with the TRL library. The training process leveraged specific versions of frameworks including TRL 1.0.0.dev0, Transformers 4.57.6, Pytorch 2.9.0, Datasets 4.8.3, and Tokenizers 0.22.2.
Good For
- Scientific question answering.
- Generating scientific explanations or summaries.
- Assisting with research-related text generation.
- Applications requiring deep contextual understanding in scientific domains.