Instructions to use Sebastianpinar/lora2-54 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora2-54 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora2-54") 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("Sebastianpinar/lora2-54") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora2-54") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f62e2d0f46696a32d765ff1cdaf05d841035d97734bb10d0c089a517f6b7ccea
- Size of remote file:
- 1.22 GB
- SHA256:
- 8649b828a1aa8fb5ac673de5713ce88959a53e761345b3210ff8e0885bb30749
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