Phi-3.5-mini-instruct-8Bit-GPTQ-c4
| Property | Value |
|---|---|
| Parameter Count | 1.14B |
| Model Type | Text Generation |
| Precision | 8-bit GPTQ |
| Downloads | 15,478 |
| Tensor Type | I32, BF16 |
What is Phi-3.5-mini-instruct-8Bit-GPTQ-c4?
Phi-3.5-mini-instruct-8Bit-GPTQ-c4 is a quantized version of the Phi-3.5 model, optimized for efficient deployment while maintaining performance. This model represents a significant achievement in balancing model capability with computational efficiency, utilizing 8-bit GPTQ quantization to reduce memory requirements while preserving model quality.
Implementation Details
The model implements several key technical innovations:
- 8-bit precision using GPTQ quantization for reduced memory footprint
- Transformer-based architecture optimized for text generation
- Compatible with text-generation-inference systems
- Hybrid tensor type support (I32 and BF16)
- Custom code implementation for optimal performance
Core Capabilities
- Efficient text generation with reduced memory requirements
- Instruction-following capabilities
- Optimized for inference deployment
- Balanced performance and resource utilization
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its efficient 8-bit quantization while maintaining the core capabilities of the Phi-3.5 architecture, making it particularly suitable for deployment in resource-constrained environments.
Q: What are the recommended use cases?
The model is well-suited for text generation tasks where efficient deployment is crucial, particularly in scenarios requiring instruction-following capabilities with limited computational resources.
