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:
- 4e33a94609de85d194500cf10fbf5069bfdb00659796eca59353b6bb5ce46b9a
- Size of remote file:
- 14.6 kB
- SHA256:
- a120b86f8a289cccf43565c86dae0ff50f3aa66a4162fe5f05c5661b52985504
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.