Instructions to use LanguageBind/LanguageBind_Video_V1.5_FT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LanguageBind/LanguageBind_Video_V1.5_FT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-image-classification", model="LanguageBind/LanguageBind_Video_V1.5_FT") 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_Video_V1.5_FT", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3acb9d5d58f2390d68d7415083fb599ee9258136f1f69eef435c2fff01fe22fc
- Size of remote file:
- 2.11 GB
- SHA256:
- 679550de18a870da915eeb6ed32960a632d704d403815633d80b4d31ee21629d
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