LLaMA-3-8B-BNB-4Bit Model
| Property | Value |
|---|---|
| Parameter Count | 4.65B |
| Model Type | Language Model (LLaMA 3) |
| License | LLaMA 3 License |
| Quantization | 4-bit precision (BitsAndBytes) |
| Context Length | 8K tokens |
What is llama-3-8b-bnb-4bit?
This is a highly optimized version of Meta's LLaMA 3 8B parameter model, quantized to 4-bit precision using the BitsAndBytes library. It represents a significant advancement in efficient AI deployment, offering 2.4x faster inference speeds while reducing memory usage by 58% compared to standard implementations.
Implementation Details
The model leverages advanced quantization techniques to compress the original LLaMA 3 architecture while maintaining performance. It's specifically designed for deployment scenarios where computational efficiency is crucial.
- 4-bit quantization for reduced memory footprint
- Optimized for both CPU and GPU deployment
- Supports multiple tensor types (F32, BF16, U8)
- Compatible with Hugging Face Transformers library
Core Capabilities
- Achieves 68.4 points on MMLU (5-shot)
- Strong performance on math and reasoning tasks (79.6% on GSM-8K)
- Maintains the 8K token context window of the original model
- Efficient text generation and completion tasks
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its exceptional balance between performance and efficiency, achieving near-original model accuracy while significantly reducing computational requirements through advanced 4-bit quantization.
Q: What are the recommended use cases?
The model is ideal for production deployments where resource efficiency is crucial, particularly suitable for text generation, completion tasks, and general language understanding applications. It's especially valuable for deployments with limited computational resources.
