Feature Extraction
Transformers
Safetensors
medical
radiology
vision-language
chest-ct
3d-medical-imaging
glint
custom_code
Instructions to use Deepnoid/GLINT-CT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Deepnoid/GLINT-CT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Deepnoid/GLINT-CT", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Deepnoid/GLINT-CT", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download data/splits/msd_lung/test.txt from Deepnoid/GLINT-CT: direct link, hf CLI and curl.
- Browser
- Download file 117 Bytes
-
https://huggingface.co/Deepnoid/GLINT-CT/resolve/main/data/splits/msd_lung/test.txt
- Command line
-
hf download hf://Deepnoid/GLINT-CT/data/splits/msd_lung/test.txt
-
curl -L -o test.txt https://huggingface.co/Deepnoid/GLINT-CT/resolve/main/data/splits/msd_lung/test.txt
117 Bytes
| lung_005 | |
| lung_016 | |
| lung_022 | |
| lung_023 | |
| lung_027 | |
| lung_028 | |
| lung_041 | |
| lung_051 | |
| lung_059 | |
| lung_071 | |
| lung_073 | |
| lung_081 | |
| lung_093 | |