Instructions to use namnh2002/model_timesformer_subset_02 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use namnh2002/model_timesformer_subset_02 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="namnh2002/model_timesformer_subset_02")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("namnh2002/model_timesformer_subset_02") model = AutoModelForVideoClassification.from_pretrained("namnh2002/model_timesformer_subset_02", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from namnh2002/model_timesformer_subset_02: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/namnh2002/model_timesformer_subset_02/resolve/main/training_args.bin
- Command line
-
hf download hf://namnh2002/model_timesformer_subset_02/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/namnh2002/model_timesformer_subset_02/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- f5712c8ccd6cef1ee72c0ab85fd1df912f9e009019f1391a12d6c74914f7b23c
- Size of remote file:
- 4.98 kB
- SHA256:
- da16ef5a3bdc71ab7383f3108078db4ccbed072a06454f0566bf438645d409af
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