Instructions to use 2nzi/videomae-surf-analytics with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 2nzi/videomae-surf-analytics with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("video-classification", model="2nzi/videomae-surf-analytics")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForVideoClassification processor = AutoImageProcessor.from_pretrained("2nzi/videomae-surf-analytics") model = AutoModelForVideoClassification.from_pretrained("2nzi/videomae-surf-analytics", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download all-data.zip from 2nzi/videomae-surf-analytics: direct link, hf CLI and curl.
- Browser
- Download file 3.96 GB
-
https://huggingface.co/2nzi/videomae-surf-analytics/resolve/main/all-data.zip
- Command line
-
hf download hf://2nzi/videomae-surf-analytics/all-data.zip
-
curl -L -o all-data.zip https://huggingface.co/2nzi/videomae-surf-analytics/resolve/main/all-data.zip
3.96 GB
- Xet hash:
- 980b115cfef137082a55c5875f65bdc93869954cc3541c4bbef6686b365c65d7
- Size of remote file:
- 3.96 GB
- SHA256:
- 021bee406cf3d1b980c04e37fccce720015207176779c2311ed5dba096808df7
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