Phi-3.5-mini-instruct-GGUF
| Property | Value |
|---|---|
| Parameter Count | 3.82B |
| Model Type | Text Generation / Conversational |
| Quantization Options | 2-bit to 8-bit precision |
| Original Creator | Microsoft |
| Conversion Author | MaziyarPanahi |
What is Phi-3.5-mini-instruct-GGUF?
Phi-3.5-mini-instruct-GGUF is a quantized version of Microsoft's Phi-3.5-mini-instruct model, converted to the GGUF format for optimal performance and compatibility with various inference frameworks. This conversion enables efficient local deployment while maintaining the model's core capabilities.
Implementation Details
The model has been converted to GGUF format, which is the successor to GGML, offering improved compatibility and performance. It provides multiple quantization options ranging from 2-bit to 8-bit precision, allowing users to balance between model size and accuracy based on their specific needs.
- Multiple quantization options (2-bit to 8-bit)
- GGUF format optimization
- Compatibility with major inference frameworks
- Optimized for local deployment
Core Capabilities
- Text generation and instruction following
- Conversational AI applications
- Efficient local inference
- Cross-platform compatibility
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its efficient implementation of Microsoft's Phi-3.5 architecture in GGUF format, offering various quantization options while maintaining good performance. It's particularly suitable for users seeking a balance between model capability and resource efficiency.
Q: What are the recommended use cases?
The model is well-suited for text generation tasks, conversational applications, and instruction-following scenarios. It's particularly valuable for users who need to run inference locally with limited computational resources.
