Neelectric/Llama-3.1-8B-Instruct_SFT_mathv00.02_s44
Neelectric/Llama-3.1-8B-Instruct_SFT_mathv00.02_s44 is an 8 billion parameter instruction-tuned language model, fine-tuned from Meta's Llama-3.1-8B-Instruct. This model, developed by Neelectric, has been specifically trained using Supervised Fine-Tuning (SFT) with the TRL framework. It is designed for general instruction-following tasks, leveraging its 32768 token context length for comprehensive responses.
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Model Overview
Neelectric/Llama-3.1-8B-Instruct_SFT_mathv00.02_s44 is an 8 billion parameter instruction-tuned language model, building upon Meta's Llama-3.1-8B-Instruct. This model has undergone Supervised Fine-Tuning (SFT) using the TRL framework, indicating a focus on improving its ability to follow instructions and generate coherent responses based on provided prompts.
Key Capabilities
- Instruction Following: Enhanced through SFT, the model is designed to accurately interpret and respond to user instructions.
- Base Model Heritage: Benefits from the robust architecture and pre-training of the Llama-3.1-8B-Instruct base model.
- Context Handling: Supports a substantial context length of 32768 tokens, allowing for processing and generating longer, more detailed interactions.
Training Details
The model was fine-tuned using the TRL (Transformers Reinforcement Learning) library, a framework commonly used for fine-tuning large language models. The training process involved SFT, which typically uses high-quality, human-annotated data to guide the model's behavior towards desired outputs. Specific details regarding the dataset used for SFT are not provided in the model card, but the methodology suggests an emphasis on refining its conversational and instructional abilities.