Instructions to use marshmellow77/roberta-base-cuad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marshmellow77/roberta-base-cuad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="marshmellow77/roberta-base-cuad")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("marshmellow77/roberta-base-cuad") model = AutoModelForQuestionAnswering.from_pretrained("marshmellow77/roberta-base-cuad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b2fcc71005aef46ba73a8745ad6aac997ae1c01232a09584b7db6ef22495277c
- Size of remote file:
- 496 MB
- SHA256:
- 251347208d8d5bfda2eecf1fd675ac63c710977b053241d900239c8d7dd188e0
路
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.