Instructions to use timm/regnety_1280.seer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/regnety_1280.seer with timm:
import timm model = timm.create_model("hf_hub:timm/regnety_1280.seer", pretrained=True) - Transformers
How to use timm/regnety_1280.seer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/regnety_1280.seer")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/regnety_1280.seer", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 39fcbc9551dd2a8820786768f7ebcee3394646e5d5429dbdef5db7f1edb08c28
- Size of remote file:
- 2.55 GB
- SHA256:
- 722e8fe6e09d9359734427a9dd148b5faece70ba50631dcccf37f4c0c5e30e8e
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