task-13-microsoft-Phi-3-mini-4k-instruct
| Property | Value |
|---|---|
| Base Model | microsoft/Phi-3-mini-4k-instruct |
| Library | PEFT 0.13.2 |
| Downloads | 20,055 |
| Technologies | PEFT, TensorBoard, Safetensors |
What is task-13-microsoft-Phi-3-mini-4k-instruct?
This is a specialized adaptation of Microsoft's Phi-3-mini model using Parameter-Efficient Fine-Tuning (PEFT) techniques. The model represents an optimized version designed for instruction-following tasks with a 4K context window, leveraging advanced technologies like TensorBoard for visualization and Safetensors for efficient model weight storage.
Implementation Details
The model utilizes PEFT version 0.13.2 for fine-tuning, making it more resource-efficient compared to full model fine-tuning. It maintains compatibility with the original Phi-3-mini architecture while optimizing for specific instruction-following scenarios.
- Implements PEFT for efficient adaptation of base model parameters
- Utilizes TensorBoard for training visualization and monitoring
- Employs Safetensors for secure and efficient model weight storage
- Maintains 4K token context window from base model
Core Capabilities
- Instruction following with 4K context window
- Parameter-efficient adaptation of base model
- Optimized for resource-efficient deployment
- Compatible with TensorBoard monitoring
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its efficient adaptation of the Phi-3-mini architecture using PEFT, making it more accessible for deployment while maintaining the core capabilities of the base model. The integration with TensorBoard and Safetensors adds robust monitoring and storage capabilities.
Q: What are the recommended use cases?
The model is best suited for instruction-following tasks requiring moderate context length (up to 4K tokens). It's particularly valuable in scenarios where computational resources are limited but high-quality instruction following is needed.
