Instructions to use Sebastianpinar/lora-13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora-13 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora-13") 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/lora-13") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora-13", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 30a6335584c05fb0c83ba6a559b346871d37d21e34f8a51008b13f31347d581d
- Size of remote file:
- 346 MB
- SHA256:
- 636ce867324dc56e41ca81bff212a949bfea5c7a544e6ad2fd583c91d37efba2
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