Instructions to use ZTamas/xlm-roberta-large-squad2_impossible_long_answer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ZTamas/xlm-roberta-large-squad2_impossible_long_answer 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="ZTamas/xlm-roberta-large-squad2_impossible_long_answer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ZTamas/xlm-roberta-large-squad2_impossible_long_answer") model = AutoModelForQuestionAnswering.from_pretrained("ZTamas/xlm-roberta-large-squad2_impossible_long_answer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from ZTamas/xlm-roberta-large-squad2_impossible_long_answer: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/ZTamas/xlm-roberta-large-squad2_impossible_long_answer/resolve/main/tokenizer.json
- Command line
-
hf download hf://ZTamas/xlm-roberta-large-squad2_impossible_long_answer/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ZTamas/xlm-roberta-large-squad2_impossible_long_answer/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 9a2a6af9c918305729186f8ad7cbec7f192e2271e0297609d2d7399cad68ffc7
- Size of remote file:
- 17.1 MB
- SHA256:
- 167066c03829058ec15ff5404e54585316251e89eec3f758bced173717de5322
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