Instructions to use ltg/ltg-bert-babylm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ltg/ltg-bert-babylm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ltg/ltg-bert-babylm", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("ltg/ltg-bert-babylm", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec26d51b954f5a1d1af4e91fc9b6bcbb68cc6328917b12d03006c4e6edb2c771
- Size of remote file:
- 418 MB
- SHA256:
- 2b8d6ac85c1cd6a7df8267b75b1b1403372ca61eb3b267ec3a41f160ab19aad6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.