priteshraj
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README.md
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- medical
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#
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## Overview
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While the model is open-source to foster innovation, a proprietary version with enhanced clinical applications is under active development.
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3. **Research Enablement**: Provide insights for researchers working on medical datasets.
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## Installation
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To use
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### Step 1: Clone the Repository
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```bash
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git clone https://github.com/yourusername/
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cd
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```
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### Step 2: Install Dependencies
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "yourusername/
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name)
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- **Training Time**: 15 hours for fine-tuning on a medical dataset of 50,000 samples (depending on the hardware used).
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- **Inference Latency**: ~300ms per sample on a single A100 GPU for text analysis, and ~500ms for image analysis.
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These evaluation results show that
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## Model Card
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### License
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### Base Model
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- **Architecture**: Meta-Llama/Llama-3.2-11B-Vision-Instruct
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- Healthcare
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### Roadmap
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While
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- Real-time patient monitoring capabilities.
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- Enhanced diagnostic accuracy with custom-trained datasets.
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- Proprietary algorithms for predictive analytics.
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Stay tuned for updates!
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### Contribution
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We welcome contributions from the community to make
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### Disclaimer
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### Acknowledgements
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This project is made possible thanks to:
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- medical
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# quro1: Small Medical AI Model
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## Overview
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quro1 is a compact, open-source medical AI model designed to empower healthcare professionals and researchers with advanced natural language and vision-based medical insights. Built on the robust Meta-Llama/Llama-3.2-11B-Vision-Instruct architecture, quro1 combines language understanding and image analysis to assist in transforming medical data into actionable insights.
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While the model is open-source to foster innovation, a proprietary version with enhanced clinical applications is under active development.
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3. **Research Enablement**: Provide insights for researchers working on medical datasets.
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## Installation
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To use quro1, ensure you have Python 3.8+ and the necessary dependencies installed.
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### Step 1: Clone the Repository
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```bash
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git clone https://github.com/yourusername/quro1.git
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cd quro1
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```
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### Step 2: Install Dependencies
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_name = "yourusername/quro1"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(model_name)
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- **Training Time**: 15 hours for fine-tuning on a medical dataset of 50,000 samples (depending on the hardware used).
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- **Inference Latency**: ~300ms per sample on a single A100 GPU for text analysis, and ~500ms for image analysis.
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These evaluation results show that quro1 excels in multiple domains of healthcare AI, offering both high accuracy in medical text understanding and strong performance in image analysis tasks.
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## Model Card
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### License
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quro1 is licensed under the MIT License, encouraging widespread use and adaptation.
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### Base Model
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- **Architecture**: Meta-Llama/Llama-3.2-11B-Vision-Instruct
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- Healthcare
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### Roadmap
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While quro1 remains an open-source initiative, we are actively developing a proprietary version. This closed-source version will include:
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- Real-time patient monitoring capabilities.
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- Enhanced diagnostic accuracy with custom-trained datasets.
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- Proprietary algorithms for predictive analytics.
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Stay tuned for updates!
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### Contribution
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We welcome contributions from the community to make quro1 better. Feel free to fork the repository and submit pull requests. For feature suggestions, please create an issue in the repository.
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### Disclaimer
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quro1 is a tool designed to assist healthcare professionals and researchers. It is not a replacement for professional medical advice, diagnosis, or treatment. Always consult a qualified healthcare provider for medical concerns.
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### Acknowledgements
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This project is made possible thanks to:
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