Instructions to use SummerChiam/pond_image_classification_7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SummerChiam/pond_image_classification_7 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SummerChiam/pond_image_classification_7") 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("SummerChiam/pond_image_classification_7") model = AutoModelForImageClassification.from_pretrained("SummerChiam/pond_image_classification_7", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from SummerChiam/pond_image_classification_7: direct link, hf CLI and curl.
- Browser
- Download file 343 MB
-
https://huggingface.co/SummerChiam/pond_image_classification_7/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://SummerChiam/pond_image_classification_7/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/SummerChiam/pond_image_classification_7/resolve/main/pytorch_model.bin
343 MB
- Xet hash:
- 505f7f5d312196378a1ae1beedee2ea9f602971d1a99c96ec9fe54619dc091ef
- Size of remote file:
- 343 MB
- SHA256:
- dc8a620cd61d71c700aa782edfd1f19743fbf763a1531a38b124f921ad607163
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