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")
# 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")
https://huggingface.co/KETI-NLP/vit-patch16-384-roberta-base/resolve/main/tokenizer.json
hf download hf://KETI-NLP/vit-patch16-384-roberta-base/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/KETI-NLP/vit-patch16-384-roberta-base/resolve/main/tokenizer.json
