Instructions to use gaussalgo/xlm-roberta-large_extractive-QA_en-cs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gaussalgo/xlm-roberta-large_extractive-QA_en-cs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="gaussalgo/xlm-roberta-large_extractive-QA_en-cs")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("gaussalgo/xlm-roberta-large_extractive-QA_en-cs") model = AutoModelForQuestionAnswering.from_pretrained("gaussalgo/xlm-roberta-large_extractive-QA_en-cs") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ca5dd9854aa20d75be09c2b57fb2e8bbe757d9868f26b234ca4be3049ec1a0af
- Size of remote file:
- 2.24 GB
- SHA256:
- 413d13907e00f9a47bec38d4b6ebab533489696654bd1353d5c230abc7215cb1
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