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:
- d9c5ec364fa5338657d2ec7e0d643d15dd63ff938399440900e15a6134c99497
- Size of remote file:
- 627 Bytes
- SHA256:
- 0b33a6021ef38c80e37c9e57eeee2d9cde292b81e2387b37ef5c343f0a936e12
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.