Zero-Shot Image Classification
OpenCLIP
English
vision
image-text-to-text
medical
dermatology
multimodal
foundation-model
vision-language
clip
zero-shot-classification
image-classification
concept-discovery
sparse-autoencoder
Instructions to use redlessone/DermFM-Zero with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- OpenCLIP
How to use redlessone/DermFM-Zero with OpenCLIP:
import open_clip model, preprocess_train, preprocess_val = open_clip.create_model_and_transforms('hf-hub:redlessone/DermFM-Zero') tokenizer = open_clip.get_tokenizer('hf-hub:redlessone/DermFM-Zero') - Notebooks
- Google Colab
- Kaggle
Access DermFM-Zero weights
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DermFM-Zero is released under CC BY-NC-ND 4.0 for non-commercial academic research. Please tell us briefly who you are and how you plan to use the model; this helps us track usage and report impact to our funders. Access is granted automatically.
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