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:
- 4353475bd119ea86f6e1f967fa4716d9dfa7ca3265e8c3fc0fbb8decb6581ac6
- Size of remote file:
- 4.22 kB
- SHA256:
- b864145f7b9b50f7413c2a3d931d5edc593006ae583eb3760b06d4f9528d7f86
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.