Instructions to use KETI-NLP/vit-patch16-384-roberta-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KETI-NLP/vit-patch16-384-roberta-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="KETI-NLP/vit-patch16-384-roberta-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("KETI-NLP/vit-patch16-384-roberta-base") model = AutoModel.from_pretrained("KETI-NLP/vit-patch16-384-roberta-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from KETI-NLP/vit-patch16-384-roberta-base: direct link, hf CLI and curl.
- Browser
- Download file 849 MB
-
https://huggingface.co/KETI-NLP/vit-patch16-384-roberta-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://KETI-NLP/vit-patch16-384-roberta-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/KETI-NLP/vit-patch16-384-roberta-base/resolve/main/pytorch_model.bin
849 MB
- Xet hash:
- e53923686264f629b24e2792c69dd8226f12f1558abe1ca0acb137b2c1281e65
- Size of remote file:
- 849 MB
- SHA256:
- 188d22eb222a491c6e26a07b36b12e793b3f85e29e1f2c8daf5f94b88d5409b0
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