Instructions to use VatsalPatel18/MultiOmicsGraphAttentionAutoencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use VatsalPatel18/MultiOmicsGraphAttentionAutoencoder with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("VatsalPatel18/MultiOmicsGraphAttentionAutoencoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6229e96a438b296fd6a21be7662becb3e471ae27c2852ca85b32ce5df5e9b2dc
- Size of remote file:
- 1.45 MB
- SHA256:
- a9aa745db7dfdf4da177e775fc985b45f00b6a12550945c4b0ef71dec2d7a547
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