Instructions to use Bazaar/cv_chinese_medicine_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bazaar/cv_chinese_medicine_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Bazaar/cv_chinese_medicine_classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Bazaar/cv_chinese_medicine_classification") model = AutoModelForImageClassification.from_pretrained("Bazaar/cv_chinese_medicine_classification") - Notebooks
- Google Colab
- Kaggle
cv_chinese_medicine_classification
Autogenerated by HuggingPics🤗🖼️
Create your own image classifier for anything by running the demo on Google Colab.
Report any issues with the demo at the github repo.
Example Images
baihe
dangshen
gouqi
huaihua
jinyinhua
- Downloads last month
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Evaluation results
- Accuracyself-reported0.970




