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", device_map="auto")# 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 85ec637aa696d6c40e4574bb0584bdde6e72d75818595f8dda3b25001d4ea199
- Size of remote file:
- 1.11 GB
- SHA256:
- a411a4b14a33fac196861ec6116df3827bf89d53cebe3d130dfd870d1810d526
路
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