Instructions to use SajjadAyoubi/clip-fa-vision with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SajjadAyoubi/clip-fa-vision with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SajjadAyoubi/clip-fa-vision")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SajjadAyoubi/clip-fa-vision") model = AutoModel.from_pretrained("SajjadAyoubi/clip-fa-vision", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SajjadAyoubi/clip-fa-vision: direct link, hf CLI and curl.
- Browser
- Download file 350 MB
-
https://huggingface.co/SajjadAyoubi/clip-fa-vision/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SajjadAyoubi/clip-fa-vision/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SajjadAyoubi/clip-fa-vision/resolve/main/pytorch_model.bin
350 MB
- Xet hash:
- 7cece1e95330ca9884139c952d2de4d94d71eed9b82602c54f303d63037d117b
- Size of remote file:
- 350 MB
- SHA256:
- 126ba7e533b4e01654f4a047b5932a680da34aeddc60a2db8a9f2691c23dbf68
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