Instructions to use nhanv/electra-large-vn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nhanv/electra-large-vn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="nhanv/electra-large-vn")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("nhanv/electra-large-vn") model = AutoModelForMaskedLM.from_pretrained("nhanv/electra-large-vn") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 65f5c41d1d4f76cef302a75daf1ee3f899a7eacdc39552f7aa6559af125ac7c0
- Size of remote file:
- 1.47 GB
- SHA256:
- 4579de6a7758c21b47b96b15583818753560a26010abf16db83dc0f45ed92074
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.