Model Overview

JoaoReiz/Llama3.2_3B_cachacaNER is a 3.2 billion parameter Llama 3.2 instruction-tuned model, developed by JoaoReiz. It was fine-tuned from the unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit base model, utilizing the Unsloth library and Huggingface's TRL library. This combination allowed for a significantly faster training process, specifically noted as 2x faster.

Key Characteristics

• Base Model: Fine-tuned from a Llama 3.2 3B instruction-tuned variant.
• Efficient Training: Leverages Unsloth for accelerated fine-tuning, reducing training time.
• Context Length: Supports a context window of 32768 tokens, enabling it to handle extensive input sequences.

Potential Use Cases

This model is particularly well-suited for applications where a compact yet capable Llama 3.2-based model is required, especially when efficient fine-tuning was a priority. Its instruction-tuned nature makes it adaptable for various natural language understanding and generation tasks, benefiting from the extended context length for more complex interactions.