Zero-Shot Image Classification
Transformers
PyTorch
Chinese
altclip
Zero-Shot Image Classification
bilingual
en
English
Chinese
Instructions to use BAAI/AltCLIP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BAAI/AltCLIP with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="BAAI/AltCLIP") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoProcessor, AutoModelForZeroShotImageClassification processor = AutoProcessor.from_pretrained("BAAI/AltCLIP") model = AutoModelForZeroShotImageClassification.from_pretrained("BAAI/AltCLIP") - Notebooks
- Google Colab
- Kaggle
Commit ·
3ad1276
1
Parent(s): 80c15ee
Delete tokenizer_config.json
Browse files- tokenizer_config.json +0 -22
tokenizer_config.json
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{
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"bos_token": "<s>",
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"cls_token": "<s>",
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"eos_token": "</s>",
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"mask_token": {
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"__type": "AddedToken",
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"content": "<mask>",
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"lstrip": true,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"model_max_length": 512,
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"name_or_path": "/sharefs/baai-mrnd/yzd/test/xlm-roberta-large",
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"pad_token": "<pad>",
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"processor_class": "CHCLIPProcess",
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"sep_token": "</s>",
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"sp_model_kwargs": {},
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"special_tokens_map_file": null,
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"tokenizer_class": "XLMRobertaTokenizer",
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"unk_token": "<unk>"
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}
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