Instructions to use alon-albalak/xlm-roberta-base-xquad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alon-albalak/xlm-roberta-base-xquad with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("question-answering", model="alon-albalak/xlm-roberta-base-xquad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("alon-albalak/xlm-roberta-base-xquad") model = AutoModelForQuestionAnswering.from_pretrained("alon-albalak/xlm-roberta-base-xquad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from alon-albalak/xlm-roberta-base-xquad: direct link, hf CLI and curl.
- Browser
- Download file 239 Bytes
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https://huggingface.co/alon-albalak/xlm-roberta-base-xquad/resolve/main/special_tokens_map.json
- Command line
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hf download hf://alon-albalak/xlm-roberta-base-xquad/special_tokens_map.json
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curl -L -o special_tokens_map.json https://huggingface.co/alon-albalak/xlm-roberta-base-xquad/resolve/main/special_tokens_map.json
239 Bytes
| {"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": false}} |