Transformers
PyTorch
English
language-model
graph-attention
adaptive-depth
temporal-decay
efficient-llm
Eval Results (legacy)
Instructions to use vigneshwar234/TemporalMesh-Transformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vigneshwar234/TemporalMesh-Transformer with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("vigneshwar234/TemporalMesh-Transformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 301feb69e12e82e977a4ed65e8f81714c50b2913608a594d446ee723bd0f5748
- Size of remote file:
- 406 kB
- SHA256:
- b2c29a69caacdedd98a4b7528bf6806143d6dc74661a1785eb13e64734433562
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