Meta-Llama-3.1-8B-bnb-4bit
| Property | Value |
|---|---|
| Parameter Count | 4.65B parameters |
| Context Length | 128k tokens |
| License | Llama 3.1 |
| Research Paper | View Paper |
| Supported Languages | English, German, French, Italian, Portuguese, Hindi, Spanish, Thai |
What is Meta-Llama-3.1-8B-bnb-4bit?
This is a 4-bit quantized version of Meta's Llama 3.1 8B model, optimized by Unsloth for efficient deployment while maintaining performance. The model represents a significant advancement in multilingual language modeling, featuring a 128k token context window and support for 8 languages.
Implementation Details
The model utilizes 4-bit precision through the bitsandbytes library, significantly reducing memory usage while maintaining model quality. It's built on the transformer architecture with Grouped-Query Attention (GQA) for improved inference scalability.
- Optimized for 4-bit inference with reduced memory footprint
- Supports multiple tensor types: F32, BF16, U8
- Implements 128k context window for long-form processing
- Uses GQA for better inference performance
Core Capabilities
- Multilingual text generation across 8 supported languages
- Strong performance on benchmarks like MMLU (69.4% accuracy)
- Code generation with 72.6% pass@1 on HumanEval
- Mathematical reasoning with 84.5% accuracy on GSM-8K
- Tool use and API interaction capabilities
Frequently Asked Questions
Q: What makes this model unique?
The model combines efficient 4-bit quantization with the advanced capabilities of Llama 3.1, offering significant memory savings while maintaining strong performance across multiple languages and tasks. Its 128k context window and GQA implementation make it particularly suitable for production deployments.
Q: What are the recommended use cases?
The model excels in multilingual dialogue, code generation, mathematical reasoning, and tool-based interactions. It's particularly well-suited for commercial applications requiring efficient deployment while maintaining high performance across multiple languages.
