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:
- 88863c7753591083e6135705076de1c81f046258f926db707e42b34cade220e3
- Size of remote file:
- 272 MB
- SHA256:
- 8607b7d16c0533b02b718514bc1849ad90c6908b6cfe4689f06d949ec36cdfc0
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.