Instructions to use CLMBR/binding-c-command-lstm-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/binding-c-command-lstm-4 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/binding-c-command-lstm-4", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8349c8cd9d2ffed893b45d1558e5be97bb384421a2ea2c6028e4b2582a179eb1
- Size of remote file:
- 544 MB
- SHA256:
- a04b8335f323550d5b13dab0140efba3951c128815e6c2db6b684677fba93a90
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.