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:
- 60022b142fd146e1e2eb07dda7075ae2d8e67456ba6fdba70cfa0c2bcaa51381
- Size of remote file:
- 111 kB
- SHA256:
- f419566c54ff3391816ad9b719bd7cae4f7eed7522735dc64cf8e3f1030c88b4
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