Image Segmentation
Transformers
Safetensors
inkdetection_resnet3d
feature-extraction
vesuvius-challenge
ink-detection
herculaneum
resnet3d
u-net
3d-segmentation
volumetric-imaging
custom_code
Instructions to use scrollprize/PHerc.1667-iteration-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use scrollprize/PHerc.1667-iteration-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-segmentation", model="scrollprize/PHerc.1667-iteration-2", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("scrollprize/PHerc.1667-iteration-2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preview_label.png from scrollprize/PHerc.1667-iteration-2: direct link, hf CLI and curl.
- Browser
- Download file 36.5 kB
-
https://huggingface.co/scrollprize/PHerc.1667-iteration-2/resolve/main/preview_label.png
- Command line
-
hf download hf://scrollprize/PHerc.1667-iteration-2/preview_label.png
-
curl -L -o preview_label.png https://huggingface.co/scrollprize/PHerc.1667-iteration-2/resolve/main/preview_label.png
36.5 kB
