Instructions to use hf-tiny-model-private/tiny-random-VideoMAEModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-VideoMAEModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-tiny-model-private/tiny-random-VideoMAEModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-VideoMAEModel") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-VideoMAEModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1113d4b4696ac41fa5577451174bbf9e9b8fdb3f06e3b60edbc704af72379ab1
- Size of remote file:
- 163 kB
- SHA256:
- 1b18c4b6f06e75964c7ebead1cfac36c1b0b645c1147e7f89376c72ac9548bc1
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