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---
license: mit
language:
- en
base_model:
- microsoft/phi-4
---
# Model Card for Microsoft-phi-4-Instruct-AutoRound-GPTQ-4bit
## Model Overview
**Model Name**: Microsoft-phi-4-Instruct-AutoRound-GPTQ-4bit
**Model Type**: Instruction-tuned, Quantized GPT-4-based language model
**Quantization**: GPTQ 4-bit
**Author**: Satwik11
**Hosted on**: Hugging Face
## Description
This model is a quantized version of the Microsoft phi-4 Instruct model, designed to deliver high performance while maintaining computational efficiency. By leveraging the GPTQ 4-bit quantization method, it enables deployment in environments with limited resources while retaining a high degree of accuracy.
The model is fine-tuned for instruction-following tasks, making it ideal for applications in conversational AI, question answering, and general-purpose text generation.
## Key Features
- **Instruction-tuned**: Fine-tuned to follow human-like instructions effectively.
- **Quantized for Efficiency**: Uses GPTQ 4-bit quantization to reduce memory requirements and inference latency.
- **Pre-trained Base**: Built on the Microsoft phi-4 framework, ensuring state-of-the-art performance on NLP tasks.
## Use Cases
- Chatbots and virtual assistants.
- Summarization and content generation.
- Research and educational applications.
- Semantic search and knowledge retrieval.
## Model Details
### Architecture
- **Base Model**: Microsoft phi-4
- **Quantization Technique**: GPTQ (4-bit)
- **Language**: English
- **Training Objective**: Instruction-following fine-tuning |