Upload README.md

README.md

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-title: DICOM Interpreter
-emoji: 📉
-colorFrom: blue
-colorTo: purple
-sdk: gradio
-sdk_version: 5.29.0
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+license: other
+license_name: nvidia-oneway-noncommercial-license
+license_link: LICENSE
+---
+
+# Llama3-VILA-M3-8B
+
+> Built with Meta Llama 3
+
+## Model Overview
+
+## Description:
+M3 is a medical visual language model that empowers medical imaging professionals, researchers, and healthcare enterprises by enhancing medical imaging workflows across various modalities. 
+
+Key features include:
+- Integration with expert models from the MONAI Model Zoo
+- Support for multiple imaging modalities
+
+For more details, see our [repo](https://github.com/Project-MONAI/VLM)
+
+### Core Capabilities
+M3 NIM provides a comprehensive suite of 2D medical image analysis tools, including:
+1. Segmentation
+2. Classification
+3. Visual Question Answering (VQA)
+4. Report/Findings Generation
+
+These capabilities are applicable across various medical imaging modalities, leveraging expert models from the MONAI Model Zoo to ensure high-quality results.
+
+## Model Architecture: 
+**Architecture Type:** Auto-Regressive Vision Language Model
+**Network Architecture:** [VILA](https://github.com/NVlabs/VILA) with Llama
+
+## Input: 
+**Input Type(s):** Text and Image
+**Input Format(s):** Text: String, Image
+**Input Parameters:** Text: 1D, Image: 2D 
+
+## Output: 
+**Output Type(s):** Text and Image 
+**Output Format:** Text: String and Image
+**Output Parameters:** Text: 1D, Image: 2D/3D 
+
+## Ethical Considerations
+NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications.  When downloaded or used in accordance with our terms of service, developers should work with their internal model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.