Instructions to use fxmarty/resnet-tiny-beans with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fxmarty/resnet-tiny-beans with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="fxmarty/resnet-tiny-beans") 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("fxmarty/resnet-tiny-beans") model = AutoModelForImageClassification.from_pretrained("fxmarty/resnet-tiny-beans", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from fxmarty/resnet-tiny-beans: direct link, hf CLI and curl.
- Browser
- Download file 787 kB
-
https://huggingface.co/fxmarty/resnet-tiny-beans/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://fxmarty/resnet-tiny-beans/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/fxmarty/resnet-tiny-beans/resolve/main/pytorch_model.bin
787 kB
- Xet hash:
- 074db4b0a226b032ebb052f9c171f0a731775782330b76f79555ecf9992d9b7c
- Size of remote file:
- 787 kB
- SHA256:
- 254ccca45caf03cc79e83c3da6c254599f47f42160414bfc5d36230d5cb990ea
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