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:
- 706aedce64030e96fe7cd0a2decc25c1df9c9e70b4fdecd96d88fd76f6bd87d3
- Size of remote file:
- 627 Bytes
- SHA256:
- 54c7050966fa1947ee1ffb6ce0befa7ed5c1fde101e75f556422854b5ef6b0ce
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.