Instructions to use skywalker290/videomae-timesformer-d1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use skywalker290/videomae-timesformer-d1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="skywalker290/videomae-timesformer-d1")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("skywalker290/videomae-timesformer-d1") model = AutoModelForVideoClassification.from_pretrained("skywalker290/videomae-timesformer-d1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from skywalker290/videomae-timesformer-d1: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/skywalker290/videomae-timesformer-d1/resolve/main/training_args.bin
- Command line
-
hf download hf://skywalker290/videomae-timesformer-d1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/skywalker290/videomae-timesformer-d1/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- 1286cf9772ad9147c93c09eef33b09f81f1e6eae21dca0723fb76427cc9ac3ca
- Size of remote file:
- 5.3 kB
- SHA256:
- d83089705cc732ff583c9eb777bb526e0370a3099b9a7512b780ccdf58bb601b
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