Instructions to use ProjectPersonal/testkndlk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ProjectPersonal/testkndlk with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ProjectPersonal/testkndlk") 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("ProjectPersonal/testkndlk") model = AutoModelForImageClassification.from_pretrained("ProjectPersonal/testkndlk", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 00167c5b42240e599f29a78ad679bacbd6a4f014bfe6fac94c4349c78abc5982
- Size of remote file:
- 343 MB
- SHA256:
- bdc6f30713c7936c257fed878884dbd2c4c21e54362496e930afbe677b955fe3
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