Instructions to use facebook/regnet-y-320-seer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/regnet-y-320-seer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="facebook/regnet-y-320-seer")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("facebook/regnet-y-320-seer") model = AutoModel.from_pretrained("facebook/regnet-y-320-seer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f4247f924eb4e5bbf9c7672901d9cb539d3cac71c4966b8bab33e4afccb93bd
- Size of remote file:
- 566 MB
- SHA256:
- f97e229da5aefd0d059811e5f83dc9ec7e69556811bfcea5d954060df84daa56
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