Satwik11/Microsoft-phi-4-Instruct-AutoRound-GPTQ-4bit

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