Mistral-7B-Instruct-v0.3-BNB-4bit
| Property | Value |
|---|---|
| Parameter Count | 3.87B |
| License | Apache 2.0 |
| Tensor Types | F32, BF16, U8 |
| Downloads | 123,001 |
What is mistral-7b-instruct-v0.3-bnb-4bit?
This is a highly optimized 4-bit quantized version of Mistral-7B-Instruct-v0.3, implemented using Unsloth's optimization techniques. The model offers significant performance improvements with 2.2x faster inference and 62% reduced memory footprint compared to the original implementation.
Implementation Details
The model utilizes bitsandbytes quantization for efficient inference while maintaining model quality. It supports multiple tensor types (F32, BF16, U8) and is specifically designed for conversational and instruction-following tasks.
- 4-bit precision quantization for memory efficiency
- Optimized using Unsloth's acceleration techniques
- Compatible with text-generation-inference endpoints
- Built on the Transformers library architecture
Core Capabilities
- Instruction-following and conversational AI tasks
- Efficient text generation with reduced memory footprint
- Support for ShareGPT ChatML / Vicuna templates
- Integration with popular deployment platforms
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its optimized performance characteristics, offering 2.2x faster inference and 62% less memory usage while maintaining the powerful capabilities of Mistral-7B-Instruct-v0.3. The 4-bit quantization makes it particularly suitable for deployment in resource-constrained environments.
Q: What are the recommended use cases?
The model is ideal for conversational AI applications, instruction-following tasks, and general text generation. It's particularly well-suited for applications requiring efficient deployment with limited computational resources, such as production environments with memory constraints.
