Instructions to use tarekziade/vit-base-patch16-224 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tarekziade/vit-base-patch16-224 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="tarekziade/vit-base-patch16-224") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("tarekziade/vit-base-patch16-224") model = AutoModelForImageClassification.from_pretrained("tarekziade/vit-base-patch16-224", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from tarekziade/vit-base-patch16-224: direct link, hf CLI and curl.
- Browser
- Download file 456 Bytes
-
https://huggingface.co/tarekziade/vit-base-patch16-224/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://tarekziade/vit-base-patch16-224/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/tarekziade/vit-base-patch16-224/resolve/main/tokenizer_config.json
456 Bytes
| { | |
| "add_prefix_space": false, | |
| "bos_token": "<|endoftext|>", | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": "<|endoftext|>", | |
| "max_length": 32, | |
| "model_max_length": 1024, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "<|endoftext|>", | |
| "pad_token_type_id": 0, | |
| "padding_side": "right", | |
| "stride": 0, | |
| "tokenizer_class": "GPT2Tokenizer", | |
| "truncation_side": "right", | |
| "truncation_strategy": "longest_first", | |
| "unk_token": "<|endoftext|>" | |
| } | |