Instructions to use SixAILab/nepa-large-patch14-224-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SixAILab/nepa-large-patch14-224-sft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="SixAILab/nepa-large-patch14-224-sft") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import ViTNepaForImageClassification model = ViTNepaForImageClassification.from_pretrained("SixAILab/nepa-large-patch14-224-sft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from SixAILab/nepa-large-patch14-224-sft: direct link, hf CLI and curl.
- Browser
- Download file 1.22 GB
-
https://huggingface.co/SixAILab/nepa-large-patch14-224-sft/resolve/main/model.safetensors
- Command line
-
hf download hf://SixAILab/nepa-large-patch14-224-sft/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/SixAILab/nepa-large-patch14-224-sft/resolve/main/model.safetensors
1.22 GB
- Xet hash:
- d53fcf532a673ed4dc2e0e13e59f4977fd075aaf1556b18c86b555fd93e5bafa
- Size of remote file:
- 1.22 GB
- SHA256:
- 2bdd6750ebe5f57a663493cf5a121f0d76ebaa28ef631890956359989ec97e40
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