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:
- f2c624d33ce6a77c532ba06657f78f207526d7d01c407075c21ffd797e455870
- Size of remote file:
- 4.22 kB
- SHA256:
- fce678cf243d5939393852448c90a079bfa0766b2f3bebdb125525299d6c880f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.