Image Classification
Transformers
Safetensors
English
model_hub_mixin
pytorch_model_hub_mixin
Eval Results (legacy)
Instructions to use X01D/6DRepNET-RepVGGA0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use X01D/6DRepNET-RepVGGA0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="X01D/6DRepNET-RepVGGA0") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("X01D/6DRepNET-RepVGGA0", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d80ef9640f0a218582f0544e8ef191613b8f98cf9fe3f13e8675c1c8c3826764
- Size of remote file:
- 28.1 MB
- SHA256:
- 39b4dd74fdbdd9941fa4bbe5fc003a02d1b53b7f3086f44c87f7f1cb3ba06cf3
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