Instructions to use roshnir/xlmr-base-trained-squadv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roshnir/xlmr-base-trained-squadv2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="roshnir/xlmr-base-trained-squadv2")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("roshnir/xlmr-base-trained-squadv2") model = AutoModelForQuestionAnswering.from_pretrained("roshnir/xlmr-base-trained-squadv2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 212bfaaf7beffc70a3f2b8fbd9929f72e086ac0287cc39a5d98486b405c9209a
- Size of remote file:
- 17.1 MB
- SHA256:
- 46afe88da5fd71bdbab5cfab5e84c1adce59c246ea5f9341bbecef061891d0a7
路
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