Instructions to use arman-aminian/clip-farsi-vision-MGXRW with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arman-aminian/clip-farsi-vision-MGXRW with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="arman-aminian/clip-farsi-vision-MGXRW")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("arman-aminian/clip-farsi-vision-MGXRW") model = AutoModel.from_pretrained("arman-aminian/clip-farsi-vision-MGXRW", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 424a7b5a8b026b3a171561d69879ddf15e79a8d453a54af149210cd59e8c704b
- Size of remote file:
- 350 MB
- SHA256:
- 856dff624c448c7734c3bc963215fafa47339f0723a4cff992c37e840cb61792
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