Instructions to use glazzova/body_type with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use glazzova/body_type with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="glazzova/body_type") 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("glazzova/body_type") model = AutoModelForImageClassification.from_pretrained("glazzova/body_type", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bbf94b87a758677dfd75e0a58357f18a0ef29ce26e3b3ee2ac7233edc34e53a1
- Size of remote file:
- 188 MB
- SHA256:
- 0d8955560524dcdbfbe9b6b9ae699f6ab10aaa28b0a5eaad47bb49bcb3fb84ef
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