microsoft/BiomedCLIP-PubMedBERT_256-vit_base_patch16_224
https://huggingface.co/microsoft/BiomedCLIP-PubMedBERT_256-vit_base_patch16_224BiomedCLIP is a biomedical vision-language foundation model that is pretrained on PMC-15M, a dataset of 15 million figure-caption pairs extracted from biomedical research articles in PubMed Central, using contrastive learning.
Sourced from
- HuggingFace — microsoft/BiomedCLIP-PubMedBERT_256-vit_base_patch16_224
Related resources
Vision-language model for dermatology, pretrained with MAGEN (Multi-Agent data GENeration) and O-MAKE (Ontology-based Multi-Aspect Knowledge-Enhanced pretraining).
BioCLIP is a foundation model for the tree of life, built using CLIP architecture as a vision model for general organismal biology. It is trained on TreeOfLife-10M, our specially-created dataset covering over 450K taxa--the most biologically diverse ML-ready dataset available to date.
## Model Description This is a lightweight, high-performance image classification model built to diagnose histopathological scans of lung and colon tissues. This model was specifically designed for rapid web deployment without sacrificing clinical accuracy.
FreedomIntelligence/Apollo2-2B
by FreedomIntelligenceCovering 12 Major Languages including English, Chinese, French, Hindi, Spanish, Arabic, Russian, Japanese, Korean, German, Italian, Portuguese and 38 Minor Languages So far.
westlake-repl/Evolla-10B
by westlake-replA frontier protein-language generative model — because proteins deserve better small talk.