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:
- 9cf8199bbf0d93f42625dee17433000fe55e83d30568e487b834b1422ff44be2
- Size of remote file:
- 295 MB
- SHA256:
- 84d735c36f7917091b19de19b10d1614f4d06381074781a761c174f2dab1ce9a
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