Instructions to use Hemg/Birdsclassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hemg/Birdsclassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Hemg/Birdsclassification") 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("Hemg/Birdsclassification") model = AutoModelForImageClassification.from_pretrained("Hemg/Birdsclassification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f75449387bee9011f52c2632b24d8624a98e0b4615a00663ba714b6e9209bf35
- Size of remote file:
- 4.92 kB
- SHA256:
- 473d022c37eb2ffa5fa9cfa370d906d22609fd112fe6292cfedc6a6dcba7e746
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