Zero-Shot Image Classification
Transformers
English
medical
multimodal
vision-language pre-training
chest x-ray
Instructions to use pykale/MeDSLIP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pykale/MeDSLIP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="pykale/MeDSLIP") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("pykale/MeDSLIP", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Improve model card: Add library_name and correct pipeline_tag
#1
by nielsr HF Staff - opened
This PR improves the model card by:
- Correcting the
pipeline_tagtoimage-text-to-textto accurately reflect the model's functionality. - Adding the
library_nameto the metadata for improved discoverability.
wenruifan changed pull request status to merged