Instructions to use google/electra-base-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/electra-base-generator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google/electra-base-generator")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google/electra-base-generator") model = AutoModelForMaskedLM.from_pretrained("google/electra-base-generator") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 16bf679c7c39227ba1d7586c760c55866c6dbc0d1c70a66eaa8dc2af981d8652
- Size of remote file:
- 135 MB
- SHA256:
- 1ba1ca8e3207546a6ac04801d6985a8674915a8922e5f05b3056b246ea12a123
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.