Neelectric/Llama-3.1-8B-Instruct_SFT_sciencev00.05
Neelectric/Llama-3.1-8B-Instruct_SFT_sciencev00.05 is an 8 billion parameter instruction-tuned causal language model developed by Neelectric, fine-tuned from Meta's Llama-3.1-8B-Instruct. With a 32,768 token context length, this model is specifically optimized for scientific reasoning tasks. It leverages a specialized dataset for fine-tuning, making it particularly adept at handling complex scientific queries and discussions.
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Neelectric/Llama-3.1-8B-Instruct_SFT_sciencev00.05 Overview
This model is an 8 billion parameter instruction-tuned language model, developed by Neelectric, building upon the robust Meta Llama-3.1-8B-Instruct architecture. It features a substantial context length of 32,768 tokens, enabling it to process and generate extensive scientific content.
Key Capabilities
- Specialized Scientific Reasoning: Fine-tuned on the
Neelectric/Replay_0.01.MoT_science.wildguardmix_reasoning.Llama3_4096toksdataset, this model is specifically optimized for scientific reasoning and understanding complex scientific concepts. - Instruction Following: Inherits strong instruction-following capabilities from its base Llama-3.1-8B-Instruct model, enhanced for scientific contexts.
- Extended Context: The 32,768 token context window allows for in-depth analysis and generation of responses based on large scientific texts or complex problem descriptions.
Training Details
The model was trained using Supervised Fine-Tuning (SFT) with the TRL framework, ensuring a focused adaptation to scientific domain knowledge. The training procedure utilized specific versions of TRL, Transformers, Pytorch, Datasets, and Tokenizers, as detailed in the original model card.