Instructions to use qubvel-hf/vjepa2-vitg-fpc64-384-ssv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use qubvel-hf/vjepa2-vitg-fpc64-384-ssv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="qubvel-hf/vjepa2-vitg-fpc64-384-ssv2")# Load model directly from transformers import AutoTokenizer, AutoModelForVideoClassification tokenizer = AutoTokenizer.from_pretrained("qubvel-hf/vjepa2-vitg-fpc64-384-ssv2") model = AutoModelForVideoClassification.from_pretrained("qubvel-hf/vjepa2-vitg-fpc64-384-ssv2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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library_name: transformers
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datasets:
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- HuggingFaceM4/something_something_v2
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# V-JEPA 2
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library_name: transformers
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datasets:
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- HuggingFaceM4/something_something_v2
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base_model:
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- facebook/vjepa2-vitg-fpc64-384
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# V-JEPA 2
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