Llama-3.2-3B-Instruct-4bit
| Property | Value |
|---|---|
| Parameter Count | 502M |
| Model Type | Instruction-tuned LLM |
| Quantization | 4-bit precision |
| Framework | MLX |
| License | Llama 3.2 |
| Supported Languages | 8 (en, de, fr, it, pt, hi, es, th) |
What is Llama-3.2-3B-Instruct-4bit?
This model is a highly optimized 4-bit quantized version of Meta's Llama-3.2-3B-Instruct, specifically adapted for the MLX framework. It represents a significant advancement in efficient AI deployment, offering the powerful capabilities of the Llama 3.2 architecture in a more compact and accessible format.
Implementation Details
The model has been converted to MLX format using mlx-lm version 0.18.2, featuring FP16 and U32 tensor types. The 4-bit quantization significantly reduces the model's memory footprint while maintaining performance.
- Efficient 4-bit precision quantization
- MLX framework optimization
- Multi-language support for 8 languages
- Streamlined deployment pipeline
Core Capabilities
- Text generation and completion tasks
- Multi-language processing
- Instruction-following capabilities
- Efficient inference with reduced memory requirements
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its efficient 4-bit quantization while maintaining the core capabilities of Llama 3.2, specifically optimized for MLX framework users. It offers a perfect balance between performance and resource efficiency.
Q: What are the recommended use cases?
The model is ideal for applications requiring multilingual text generation and instruction-following capabilities, particularly in resource-constrained environments where model efficiency is crucial.
