Instructions to use NeuronZero/WBC-Classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NeuronZero/WBC-Classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="NeuronZero/WBC-Classifier") 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("NeuronZero/WBC-Classifier") model = AutoModelForImageClassification.from_pretrained("NeuronZero/WBC-Classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from NeuronZero/WBC-Classifier: direct link, hf CLI and curl.
- Browser
- Download file 94.4 MB
-
https://huggingface.co/NeuronZero/WBC-Classifier/resolve/main/model.safetensors
- Command line
-
hf download hf://NeuronZero/WBC-Classifier/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/NeuronZero/WBC-Classifier/resolve/main/model.safetensors
94.4 MB
- Xet hash:
- 8579bbd24033ff7fb709a1892d33677cb67d7516694765b95884d874ac552935
- Size of remote file:
- 94.4 MB
- SHA256:
- eb45a381a94d542f635e7a2536e4dcf04f8a597cc80df57f1fa1732077c9fff7
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