Instructions to use facebook/regnet-y-640-seer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-y-640-seer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="facebook/regnet-y-640-seer")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("facebook/regnet-y-640-seer") model = AutoModel.from_pretrained("facebook/regnet-y-640-seer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6417c5549d39742d6a7dad81eecc7b1d134c26a1365e84e2be32c753c64f1930
- Size of remote file:
- 1.11 GB
- SHA256:
- 287562d2a6cf4ffbdc72a638d1727f892369009a94755dbb6e9ae08c4677bc58
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