Instructions to use not-lain/testpushfrommodel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use not-lain/testpushfrommodel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="not-lain/testpushfrommodel", trust_remote_code=True) pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModelForImageClassification model = AutoModelForImageClassification.from_pretrained("not-lain/testpushfrommodel", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6590b703f78e51136eb29bdb9e6b231647156e0b8a3468f70ddbf9113cc4d123
- Size of remote file:
- 88 kB
- SHA256:
- 6eee7d5198f4d57968bd06755727c4e89cd627b1b5fa7e0bfa42cf5a3bcd6697
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