Instructions to use LanguageBind/LanguageBind_Image with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LanguageBind/LanguageBind_Image with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="LanguageBind/LanguageBind_Image") pipe( "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png", candidate_labels=["animals", "humans", "landscape"], )# Load model directly from transformers import AutoModelForZeroShotImageClassification model = AutoModelForZeroShotImageClassification.from_pretrained("LanguageBind/LanguageBind_Image", dtype="auto") - Notebooks
- Google Colab
- Kaggle
File size: 814 Bytes
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"bos_token": {
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"lstrip": false,
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"name_or_path": "lb203/LanguageBind_Image",
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"special_tokens_map_file": "./special_tokens_map.json",
"tokenizer_class": "LanguageBindImageTokenizer",
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