Instructions to use badokorach/xlm-roberta-base-finetuned-mlqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use badokorach/xlm-roberta-base-finetuned-mlqa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="badokorach/xlm-roberta-base-finetuned-mlqa")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("badokorach/xlm-roberta-base-finetuned-mlqa") model = AutoModelForQuestionAnswering.from_pretrained("badokorach/xlm-roberta-base-finetuned-mlqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a6217ee76a707798a5efa57841a80977a690adb7d2dc2df7dd1e53015949d0cd
- Size of remote file:
- 1.11 GB
- SHA256:
- afa2ad6cca3f4762b7706cbab01b29db8a76eeebef58a9804bcb71c9be3ea481
路
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