Instructions to use timm/regnety_640.seer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/regnety_640.seer with timm:
import timm model = timm.create_model("hf_hub:timm/regnety_640.seer", pretrained=True) - Transformers
How to use timm/regnety_640.seer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="timm/regnety_640.seer")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/regnety_640.seer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b752f654771d983dce38fe00e8b1c6bd085250cec55b67554aa96a0a63f86e5a
- Size of remote file:
- 1.11 GB
- SHA256:
- 9367ef445b828b5b1e36d215072e9e1cbc7dd7bc9989d2b4c20778ab79bf9a49
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.