Instructions to use timm/bat_resnext26ts.ch_in1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- timm
How to use timm/bat_resnext26ts.ch_in1k with timm:
import timm model = timm.create_model("hf_hub:timm/bat_resnext26ts.ch_in1k", pretrained=True) - Transformers
How to use timm/bat_resnext26ts.ch_in1k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="timm/bat_resnext26ts.ch_in1k") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("timm/bat_resnext26ts.ch_in1k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1db8f5c52b07b308db3ffa9ee3e4adbf8e780217989f55a87fd81dbd66ade292
- Size of remote file:
- 43.2 MB
- SHA256:
- 2e965690115ef58f14cf221bb85459a1bb048dd8b045054336254c3d7cf12bab
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