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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2e97e91cb02d93825d76007f6b16703912e0282d885d4acec8855827d4c5e6ef
- Size of remote file:
- 1.29 kB
- SHA256:
- 4e8d5761c6cc35926f333dc830fcb61fb764359b8d7f8b5709d4ac8bb28f175d
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