Instructions to use hf-tiny-model-private/tiny-random-PoolFormerForImageClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-PoolFormerForImageClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hf-tiny-model-private/tiny-random-PoolFormerForImageClassification") 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("hf-tiny-model-private/tiny-random-PoolFormerForImageClassification") model = AutoModelForImageClassification.from_pretrained("hf-tiny-model-private/tiny-random-PoolFormerForImageClassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hf-tiny-model-private/tiny-random-PoolFormerForImageClassification: direct link, hf CLI and curl.
- Browser
- Download file 1.84 MB
-
https://huggingface.co/hf-tiny-model-private/tiny-random-PoolFormerForImageClassification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hf-tiny-model-private/tiny-random-PoolFormerForImageClassification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hf-tiny-model-private/tiny-random-PoolFormerForImageClassification/resolve/main/pytorch_model.bin
1.84 MB
- Xet hash:
- 2ca528843dfdce909bd8a89b5d40ce0f7a352159184d8f52fc51426d0913b8f2
- Size of remote file:
- 1.84 MB
- SHA256:
- d86617444e5d3e9022267800d75d1065ba6e8b1caafc85cc8c50dc630a437670
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