Instructions to use saburbutt/xlmroberta_large_tweetqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use saburbutt/xlmroberta_large_tweetqa 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="saburbutt/xlmroberta_large_tweetqa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("saburbutt/xlmroberta_large_tweetqa") model = AutoModelForQuestionAnswering.from_pretrained("saburbutt/xlmroberta_large_tweetqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from saburbutt/xlmroberta_large_tweetqa: direct link, hf CLI and curl.
- Browser
- Download file 2.24 GB
-
https://huggingface.co/saburbutt/xlmroberta_large_tweetqa/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://saburbutt/xlmroberta_large_tweetqa/pytorch_model.bin
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curl -L -o pytorch_model.bin https://huggingface.co/saburbutt/xlmroberta_large_tweetqa/resolve/main/pytorch_model.bin
2.24 GB
- Xet hash:
- 3821cb006e4469a124e5ac88a8f229e505ed392caa7f894565f2f87ffc5e9374
- Size of remote file:
- 2.24 GB
- SHA256:
- f068c7108f7d22e7c0d5ca394d2e480e765354557c7ce09e09f72876b58fe865
路
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