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README.md

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+Model Card for Microsoft-phi-4-Instruct-AutoRound-GPTQ-4bit
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+Model Overview
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+Model Name: Microsoft-phi-4-Instruct-AutoRound-GPTQ-4bitModel Type: Instruction-tuned, Quantized GPT-4-based language modelQuantization: GPTQ 4-bitAuthor: Satwik11Hosted on: Hugging Face
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+Description
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+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.
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+The model is fine-tuned for instruction-following tasks, making it ideal for applications in conversational AI, question answering, and general-purpose text generation.
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+Key Features
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+Instruction-tuned: Fine-tuned to follow human-like instructions effectively.
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+Quantized for Efficiency: Uses GPTQ 4-bit quantization to reduce memory requirements and inference latency.
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+Pre-trained Base: Built on the Microsoft phi-4 framework, ensuring state-of-the-art performance on NLP tasks.
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+Use Cases
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+Chatbots and virtual assistants.
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+Summarization and content generation.
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+Research and educational applications.
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+Semantic search and knowledge retrieval.
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+Model Details
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+Architecture
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+Base Model: Microsoft phi-4
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+Quantization Technique: GPTQ (4-bit)
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+Language: English
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+Training Objective: Instruction-following fine-tuning
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