BiomedCLIP-vit-bert-hf Open-source Model - Free Deployment to Boost Applications in the Biomedical Field

Biomedclip Vit Bert Hf

Developed by chuhac

A BiomedCLIP model implemented based on PyTorch and Huggingface frameworks, reproducing the original microsoft/BiomedCLIP-PubMedBERT_256-vit_base_patch16_224 model

Multimodal Fusion

Transformers

EnglishOpen Source License:MIT #Biomedical Zero-shot Classification #Multimodal CLIP Architecture #PubMedBERT-ViT Fusion

Downloads 4,437

Release Time : 5/8/2024

Model Overview

This is a Huggingface-compatible BiomedCLIP model for zero-shot classification tasks, combining vision and language processing capabilities, specifically optimized for the biomedical field.

Model Features

Biomedical Domain Optimization

Specifically optimized for biomedical domain data and tasks

Multimodal Model

Combines vision and language processing capabilities to handle both image and text inputs

Huggingface Compatible

Fully implemented based on PyTorch and Huggingface frameworks for easy integration and use

Model Capabilities

Zero-shot Image Classification

Multimodal Feature Extraction

Biomedical Image Understanding

Text-Image Association Analysis

Use Cases

Medical Imaging Analysis

Medical Image Classification

Zero-shot classification of medical images such as X-rays and CT scans

Biomedical Research

Literature-Image Association Analysis

Associative analysis between medical literature content and related images

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Biomedclip Vit Bert Hf

Model Overview

Model Features

Model Capabilities

Use Cases

🚀 Huggingface-friendly BiomedCLIP

🚀 Quick Start

💻 Usage Examples

Basic Usage

📄 License