Instructions to use deepset/xlm-roberta-base-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepset/xlm-roberta-base-squad2 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="deepset/xlm-roberta-base-squad2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("deepset/xlm-roberta-base-squad2") model = AutoModelForQuestionAnswering.from_pretrained("deepset/xlm-roberta-base-squad2", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from deepset/xlm-roberta-base-squad2: direct link, hf CLI and curl.
- Browser
- Download file 1.11 GB
-
https://huggingface.co/deepset/xlm-roberta-base-squad2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://deepset/xlm-roberta-base-squad2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/deepset/xlm-roberta-base-squad2/resolve/main/pytorch_model.bin
1.11 GB
- Xet hash:
- 6ba6f9cbcc9fc7444bf94170dd0b172c1a0c44bbc15e0f6b0d2d4e9db561bae7
- Size of remote file:
- 1.11 GB
- SHA256:
- faeaac92ea0e658d5f7a34a8cc42280a2261e500c647cffb37cee7e3836025bd
路
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