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
File size: 461 Bytes
e62ea39 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"add_prefix_space": false,
"bos_token": "<s>",
"cls_token": "<s>",
"eos_token": "</s>",
"errors": "replace",
"mask_token": "<mask>",
"model_max_length": 512,
"name_or_path": "./aligned-vit-patch16-384-roberta-base",
"pad_token": "<pad>",
"processor_class": "VisionTextDualEncoderProcessor",
"sep_token": "</s>",
"special_tokens_map_file": null,
"tokenizer_class": "RobertaTokenizer",
"trim_offsets": true,
"unk_token": "<unk>"
}
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