Instructions to use google/electra-small-generator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use google/electra-small-generator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="google/electra-small-generator")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("google/electra-small-generator") model = AutoModelForMaskedLM.from_pretrained("google/electra-small-generator") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe6a8ad2c40115bcb2a4b34aa2d7635ca5329134793424582275dab69548840b
- Size of remote file:
- 70.4 MB
- SHA256:
- 7e429bb09fee5b7271308e156a17400d06c026aadc531cb6605a17ab926fd522
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.