Feature Extraction
Transformers
Safetensors
PyTorch
English
spatial-transcriptomics
graph-transformer
gene-expression
finetuned
mouse-stroke
Instructions to use Bgoood/SpatialGT-MouseStroke-PT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bgoood/SpatialGT-MouseStroke-PT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Bgoood/SpatialGT-MouseStroke-PT")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Bgoood/SpatialGT-MouseStroke-PT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 94c433e3f23349cf00d775ec61748d22190cd2a37080268a6e51d6b265a8dc3b
- Size of remote file:
- 5.43 kB
- SHA256:
- 1630eb4d8cb72ad34be4003e7969222266f8312f2bc7a53fc7a6324175d04e34
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