Instructions to use Finisha-LLM/Two-fruita-classify with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Finisha-LLM/Two-fruita-classify with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Finisha-LLM/Two-fruita-classify") 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("Finisha-LLM/Two-fruita-classify") model = AutoModelForImageClassification.from_pretrained("Finisha-LLM/Two-fruita-classify", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 06054eb2a7ae8be07e0a587e7e43eeb3e572c896fd4d0f9fb7087e1f81f673b4
- Size of remote file:
- 347 MB
- SHA256:
- a0df9447f60774d69fddc23835f349c0601bdf762a0d2c6012623c62e921bee8
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