Model Overview

jfo150/llama-2-brainstems-chat is a 7 billion parameter language model, fine-tuned from the meta-llama/Llama-2-7b-chat-hf base model. The fine-tuning process involved a single epoch with a learning rate of 5e-05 and a batch size of 1, utilizing an Adam optimizer. The model was trained using Transformers 4.39.3 and Pytorch 2.2.2.

Key Characteristics

• Base Model: meta-llama/Llama-2-7b-chat-hf
• Parameter Count: 7 billion
• Context Length: 4096 tokens
• Training Frameworks: Transformers, Pytorch, Datasets, Tokenizers

Limitations and Unknowns

Detailed information regarding the specific dataset used for fine-tuning, the model's intended applications, and its performance characteristics is currently unavailable. Users should exercise caution and conduct their own evaluations to determine suitability for specific tasks, as the model's unique capabilities or primary differentiators are not specified.