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:
- 71bd7f2d4f210de41d90aac646b215572f20cba2be2f2c78b895f567582ed8bb
- Size of remote file:
- 4.22 kB
- SHA256:
- 0063768be2edbbfb642f3e983ce367daa5696176e15f0c2ef2d7dc6d9dc83eb9
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.