Instructions to use bertin-project/bertin-base-gaussian with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bertin-project/bertin-base-gaussian with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bertin-project/bertin-base-gaussian")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("bertin-project/bertin-base-gaussian") model = AutoModelForMaskedLM.from_pretrained("bertin-project/bertin-base-gaussian", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4de260d2e47921edd193c7a9f63cb135f23aff9658f925447a04f56dec7fc99c
- Size of remote file:
- 33 MB
- SHA256:
- 2d53b26a4792d9ab5a8952fb4bcab17b7e9fe9ad2cb23d2a7bb81cbd15643468
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.