Instructions to use Eveready/tmp_trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Eveready/tmp_trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Eveready/tmp_trainer") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Eveready/tmp_trainer") model = AutoModelForImageClassification.from_pretrained("Eveready/tmp_trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
a121a76 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:4d9a47a247fa65f0ad617fb603dfef3c87f6a81b4456cfa4e375761809f05e4e
size 4920
|