Instructions to use CLMBR/full-lstm-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/full-lstm-2 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/full-lstm-2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d51ce9f2395ab57a27fe7dd4b70c7cadd9d9d31915e2943ad478b01d30790a97
- Size of remote file:
- 4.22 kB
- SHA256:
- c15344eff0488b6e4413ace8ac951b38c9a7de75ab305a72ab7f5af565197136
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.