Model Overview

JoaoReiz/Llama3.2_3B_Paramopama is a 3.2 billion parameter Llama-based language model, developed by JoaoReiz. It is an instruction-tuned model, building upon the unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit base.

Key Characteristics

• Architecture: Based on the Llama family of models.
• Parameter Count: Features 3.2 billion parameters, offering a balance between performance and computational efficiency.
• Training Efficiency: This model was finetuned using Unsloth and Huggingface's TRL library, which facilitated a 2x faster training process compared to standard methods.
• Context Length: Supports a context length of 32768 tokens.

Potential Use Cases

• General Text Generation: Suitable for a wide range of language generation tasks due to its instruction-tuned nature.
• Efficient Deployment: Its relatively smaller size (3.2B parameters) combined with efficient training makes it a candidate for applications where faster inference or reduced resource consumption is critical.