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
Commit 路
c6e851c
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Parent(s): 3c52148
add sentence piece, special tokens map
Browse files- sentencepiece.bpe.model +3 -0
- special_tokens_map.json +1 -0
sentencepiece.bpe.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
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size 5069051
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special_tokens_map.json
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{"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}}
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