Instructions to use humane-lab/CFT-CLIP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use humane-lab/CFT-CLIP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="humane-lab/CFT-CLIP") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("humane-lab/CFT-CLIP") model = AutoModelForZeroShotImageClassification.from_pretrained("humane-lab/CFT-CLIP", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.1f97f75
-
Update README.md
Verified signature1ae5c5c -
Update README.md
Verified signature8d4c0cf -
Update README.md
Verified signature58d60c9 -
Update README.md
Verified signaturee856cef
-
Create README.md
Verified signaturef7100ec
-
delete:file
72d8ecd -
add:file
47b0443 -
add:file
d952030 -
add:file
e1f56c7 -
add:file
384e323 -
initial commit
Verified signature314dd93