Image Classification
Transformers
English
heritage
temple
damage-assessment
mixture-of-experts
Mixture of Experts
resnet50
efficientnet-b4
vit-base-patch16-224
yolo
Instructions to use monarch8661/moe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use monarch8661/moe with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="monarch8661/moe") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("monarch8661/moe", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1a1871f2951791944b1e2a185dc7c8a2490f15eff64cecc89e98c71c1791c210
- Size of remote file:
- 223 MB
- SHA256:
- 02951f108ac6797a0b4d3b1d7916f7dcec1e8a0701c66a5093a426ad738288ab
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