Instructions to use sail/poolformer_m36 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sail/poolformer_m36 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sail/poolformer_m36") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("sail/poolformer_m36") model = AutoModelForImageClassification.from_pretrained("sail/poolformer_m36", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sail/poolformer_m36: direct link, hf CLI and curl.
- Browser
- Download file 225 MB
-
https://huggingface.co/sail/poolformer_m36/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sail/poolformer_m36/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sail/poolformer_m36/resolve/main/pytorch_model.bin
225 MB
- Xet hash:
- d27ebf3a990a8ed398fd157c313e6884c36c7ae3340cca86a4963cb12d6008a7
- Size of remote file:
- 225 MB
- SHA256:
- 3aa551482615696e19e4142e3e741c37375ff7a2619a1c84b8c338981279a076
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