Instructions to use Master-Rapha7/mobilenetv2-typecoffee-6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Master-Rapha7/mobilenetv2-typecoffee-6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Master-Rapha7/mobilenetv2-typecoffee-6") 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("Master-Rapha7/mobilenetv2-typecoffee-6") model = AutoModelForImageClassification.from_pretrained("Master-Rapha7/mobilenetv2-typecoffee-6", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Master-Rapha7/mobilenetv2-typecoffee-6: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/Master-Rapha7/mobilenetv2-typecoffee-6/resolve/f88deff13c61fabff28dfc1b6977c5f7ac23b693/training_args.bin
- Command line
-
hf download hf://Master-Rapha7/mobilenetv2-typecoffee-6@f88deff13c61fabff28dfc1b6977c5f7ac23b693/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Master-Rapha7/mobilenetv2-typecoffee-6/resolve/f88deff13c61fabff28dfc1b6977c5f7ac23b693/training_args.bin
5.43 kB
- Xet hash:
- c9aac988d66bca18aa797f9ceb76598a51fad755d6d1945d8ab7fe8c6cbe612c
- Size of remote file:
- 5.43 kB
- SHA256:
- 978ef633324aa2ae6841852985cdc591a5f4393093404f5240dab18a9cd71d97
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