Model Overview

The gjyotin305/Llama-3.2-3B-Instruct_old_sft is a 3.2 billion parameter instruction-tuned language model. Developed by gjyotin305, this model is a fine-tuned version of the unsloth/Llama-3.2-3B-Instruct base model.

Key Characteristics

• Architecture: Based on the Llama-3.2 family, providing a robust foundation for language understanding and generation.
• Parameter Count: Features 3.2 billion parameters, offering a balance between performance and computational efficiency.
• Training Methodology: The model was fine-tuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process.
• Context Length: Supports a context length of 32768 tokens, allowing for processing longer inputs and generating more coherent responses.

Intended Use Cases

This model is suitable for a variety of instruction-following tasks, benefiting from its efficient fine-tuning and Llama-3.2 lineage. Its optimized training process suggests potential for applications where rapid deployment and good performance are desired.