Instructions to use gigasurgeon/mopping_224_16_frames_resampling_4_huge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gigasurgeon/mopping_224_16_frames_resampling_4_huge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="gigasurgeon/mopping_224_16_frames_resampling_4_huge")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("gigasurgeon/mopping_224_16_frames_resampling_4_huge") model = AutoModelForVideoClassification.from_pretrained("gigasurgeon/mopping_224_16_frames_resampling_4_huge", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from gigasurgeon/mopping_224_16_frames_resampling_4_huge: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/gigasurgeon/mopping_224_16_frames_resampling_4_huge/resolve/main/training_args.bin
- Command line
-
hf download hf://gigasurgeon/mopping_224_16_frames_resampling_4_huge/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/gigasurgeon/mopping_224_16_frames_resampling_4_huge/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- 37b0a05db14964b6d5b3c1fb553fac244ac5e15a7b10e376ff74d16692882452
- Size of remote file:
- 3.96 kB
- SHA256:
- b92ff7f37136e53fe87a5c3edb5dca1553492717619f4d3a38997d624660b3d5
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