Instructions to use kanlo/ASD_Behavour-trainining2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kanlo/ASD_Behavour-trainining2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="kanlo/ASD_Behavour-trainining2")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("kanlo/ASD_Behavour-trainining2") model = AutoModelForVideoClassification.from_pretrained("kanlo/ASD_Behavour-trainining2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from kanlo/ASD_Behavour-trainining2: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/kanlo/ASD_Behavour-trainining2/resolve/main/training_args.bin
- Command line
-
hf download hf://kanlo/ASD_Behavour-trainining2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/kanlo/ASD_Behavour-trainining2/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 1245a8f54e87d9758d33c822f1e6720c89b81319c20b206ebd0fac3d7ab1d43e
- Size of remote file:
- 5.11 kB
- SHA256:
- 5ecb8d45e32c1a17391a768324a2fab258b51994c31dd0b8a194f4084a308880
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