Instructions to use CLMBR/old-full-lstm-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CLMBR/old-full-lstm-4 with Transformers:
# Load model directly from transformers import RNNForLanguageModeling model = RNNForLanguageModeling.from_pretrained("CLMBR/old-full-lstm-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 99ba5f40f3a9cf8edffec18e271085a050d51034a10e7bb982fc15d2564b0d83
- Size of remote file:
- 272 MB
- SHA256:
- 289803341c0febb9c8ac8c4ef0ce15a0e2da7ffc4a767ceaea0374b1a76aa8d1
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.