Instructions to use lazyturtl/roomclassifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lazyturtl/roomclassifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="lazyturtl/roomclassifier") 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("lazyturtl/roomclassifier") model = AutoModelForImageClassification.from_pretrained("lazyturtl/roomclassifier") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e412c4fe50462d21e5fdbad6715e8d009dd8265f4412dc4e33da4d3b5e5bb6cf
- Size of remote file:
- 343 MB
- SHA256:
- b64738bebc8f5c9c3185d8585e99296902d29517f4e89e6e6ac573a5b8f4cc70
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