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--- |
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license: mit |
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language: |
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- en |
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base_model: |
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- microsoft/phi-4 |
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--- |
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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-4bit |
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**Model Type**: Instruction-tuned, Quantized GPT-4-based language model |
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**Quantization**: GPTQ 4-bit |
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**Author**: Satwik11 |
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**Hosted 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 |
