Instructions to use flagship/dgan-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flagship/dgan-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="flagship/dgan-model") 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("flagship/dgan-model") model = AutoModelForImageClassification.from_pretrained("flagship/dgan-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bb3b6087c6bce57a3e8994e2868914cf69b557097a1085b8a996ac7f53b40285
- Size of remote file:
- 111 MB
- SHA256:
- 890291443c28b1c2f8e94b76dc795561d636e7fb63b2a7032ecbfdf9675b73a6
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