Instructions to use Sebastianpinar/lora-21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora-21 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora-21") 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-21") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora-21", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d4dc5835ee49c52034ced859b5d6584117299178b114c0904b01f16d432e8d96
- Size of remote file:
- 346 MB
- SHA256:
- 8587eaa05d9e43479e50a9300c0432e2e1a7c72538ed04320e0d2727039d946e
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