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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 98 Bytes
2bc05c7 | 1 2 3 4 5 6 | {
"backbone_file": "",
"backbone_name": "RepVGG-A0",
"deploy": true,
"pretrained": false
} |