Neelectric/Llama-3.1-8B-Instruct_SFT_MoTv00.01
Neelectric/Llama-3.1-8B-Instruct_SFT_MoTv00.01 is an 8 billion parameter instruction-tuned language model developed by Neelectric, fine-tuned from Meta's Llama-3.1-8B-Instruct. It leverages the Neelectric/MoT_all_Llama3_4096toks dataset and TRL for supervised fine-tuning, offering a 32768 token context length. This model is optimized for generating coherent and contextually relevant text based on user instructions, making it suitable for conversational AI and general text generation tasks.
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Model Overview
Neelectric/Llama-3.1-8B-Instruct_SFT_MoTv00.01 is an 8 billion parameter instruction-tuned model, building upon the robust foundation of Meta's Llama-3.1-8B-Instruct. Developed by Neelectric, this model has undergone supervised fine-tuning (SFT) using the TRL library and the specialized Neelectric/MoT_all_Llama3_4096toks dataset.
Key Capabilities
- Instruction Following: Excels at understanding and executing user instructions to generate relevant and coherent text.
- Extended Context: Supports a substantial context length of 32768 tokens, allowing for processing and generating longer, more complex interactions.
- Fine-tuned Performance: Benefits from targeted fine-tuning on a specific dataset, enhancing its ability to handle diverse conversational and text generation tasks.
Training Details
The model was trained using the SFT method, with its training process and metrics visualized via Weights & Biases. The development utilized TRL version 0.28.0.dev0, Transformers 4.57.6, Pytorch 2.9.0, Datasets 4.5.0, and Tokenizers 0.22.2.
Good For
- Conversational AI: Generating human-like responses in chatbots and virtual assistants.
- General Text Generation: Creating various forms of text content based on prompts.
- Research and Development: Serving as a strong base model for further fine-tuning or experimentation in natural language processing applications.