Instructions to use miittnnss/idk with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use miittnnss/idk with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="miittnnss/idk") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("miittnnss/idk", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2b97e0469c1b0b54a82063dfac044876751170d9501b7f19605ab3e73f7bd2db
- Size of remote file:
- 347 MB
- SHA256:
- 57b69825605bc40fde5144c0a1c1c1ac21bd4774a64de947698b06478b37f600
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