Instructions to use dandelin/vilt-b32-mlm-itm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dandelin/vilt-b32-mlm-itm with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("dandelin/vilt-b32-mlm-itm") model = AutoModelForPreTraining.from_pretrained("dandelin/vilt-b32-mlm-itm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from dandelin/vilt-b32-mlm-itm: direct link, hf CLI and curl.
- Browser
- Download file 543 MB
-
https://huggingface.co/dandelin/vilt-b32-mlm-itm/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dandelin/vilt-b32-mlm-itm/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dandelin/vilt-b32-mlm-itm/resolve/main/pytorch_model.bin
543 MB
- Xet hash:
- 9ff590cbcc5c17b403b3028837dbd28e9626f758de34030bd9e3e4df0ad7d151
- Size of remote file:
- 543 MB
- SHA256:
- 99b347f6b7b9f7a6a6f642846aa6c84295736fac18a07e291d03c483ae3321df
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