Video Classification
Transformers
Safetensors
timesformer
retnet
action-recognition
ucf101
hmdb51
efficient-models
Instructions to use sumit7488/TimesNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sumit7488/TimesNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="sumit7488/TimesNet")# Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("sumit7488/TimesNet") model = AutoModelForVideoClassification.from_pretrained("sumit7488/TimesNet") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9bf7061b5d5e9a4f9bdcb2985ab6409250cd72c2bfad251ab1b8cfdd9d3a05f8
- Size of remote file:
- 518 MB
- SHA256:
- f6ab5b13bd6f9fb19d819c6f39dc4aef57c58eef40a3c409f56cf5cc0c913aef
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