Instructions to use sail/poolformer_m48 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sail/poolformer_m48 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sail/poolformer_m48") 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_m48") model = AutoModelForImageClassification.from_pretrained("sail/poolformer_m48", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sail/poolformer_m48: direct link, hf CLI and curl.
- Browser
- Download file 294 MB
-
https://huggingface.co/sail/poolformer_m48/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sail/poolformer_m48/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sail/poolformer_m48/resolve/main/pytorch_model.bin
294 MB
- Xet hash:
- a3511669e97cc81c65948c1c45449867756bcd4102847e801e14ef5bb58c890a
- Size of remote file:
- 294 MB
- SHA256:
- aaf402438c203e0ff5cac6678f69bb44d4cab576c73f2f564276ca05d683e675
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