Instructions to use amir7d0/CLIP-fa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amir7d0/CLIP-fa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="amir7d0/CLIP-fa") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("amir7d0/CLIP-fa") model = AutoModelForZeroShotImageClassification.from_pretrained("amir7d0/CLIP-fa") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e274f3e8f665df2518dc8bbad32ddcbb230734fa92d07c64bdfb15d2b418a158
- Size of remote file:
- 826 MB
- SHA256:
- 72e2aa2c90242720595c6e78515ca21e9e704c96d60f51215157ccc1172ea5f0
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