Instructions to use IIC/RigoBERTa-2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use IIC/RigoBERTa-2.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="IIC/RigoBERTa-2.0")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("IIC/RigoBERTa-2.0") model = AutoModelForMaskedLM.from_pretrained("IIC/RigoBERTa-2.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c778c3451eec6b549acc3ea0df90e4287ba9b34e1c29af56ccdf214897f6b4b9
- Size of remote file:
- 3.64 kB
- SHA256:
- f933cf19cab6478e019135ab5686065b168971c02f60f1ce4288c3a18dfb4b2f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.