spar-project/Llama-3.2-3B-Instruct-layers-16-to-24
TEXT GENERATIONConcurrency Cost:1Model Size:3.2BQuant:BF16Ctx Length:32kPublished:Mar 25, 2026License:apache-2.0Architecture:Transformer Open Weights Cold
The spar-project/Llama-3.2-3B-Instruct-layers-16-to-24 is a 3.2 billion parameter instruction-tuned causal language model, finetuned from unsloth/Llama-3.2-3B-Instruct. Developed by spar-project, this model was trained using Unsloth and Huggingface's TRL library, achieving a 2x speed improvement during training. It is designed for general instruction-following tasks, leveraging its efficient training methodology.
Loading preview...
Model Overview
The spar-project/Llama-3.2-3B-Instruct-layers-16-to-24 is a 3.2 billion parameter instruction-tuned language model. It is a finetuned version of unsloth/Llama-3.2-3B-Instruct, developed by spar-project.
Key Characteristics
- Efficient Training: This model was trained with a 2x speed improvement using Unsloth and Huggingface's TRL library, indicating an optimized training process.
- Instruction-Tuned: Designed to follow instructions effectively, making it suitable for a variety of conversational and task-oriented applications.
- Llama-3.2 Family: Based on the Llama-3.2 architecture, providing a foundation for strong language understanding and generation capabilities.
Potential Use Cases
- General Instruction Following: Ideal for applications requiring the model to respond to prompts and instructions.
- Chatbots and Conversational AI: Its instruction-tuned nature makes it well-suited for building interactive agents.
- Text Generation: Can be used for various text generation tasks where a smaller, efficiently trained model is preferred.