Instructions to use hansin91/image_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hansin91/image_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hansin91/image_classification") 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("hansin91/image_classification") model = AutoModelForImageClassification.from_pretrained("hansin91/image_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hansin91/image_classification: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/hansin91/image_classification/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://hansin91/image_classification/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hansin91/image_classification/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- a18e61b828bd2a4d043560d57ec853268bd86db2c236bfa91f4e5f63f91acacc
- Size of remote file:
- 343 MB
- SHA256:
- 75bb8d41a624944e11cc75aaecd470cdb2b6954b9883d71262a42b9d984da769
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