Instructions to use sunitha/AQG_CV_Squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sunitha/AQG_CV_Squad 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="sunitha/AQG_CV_Squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("sunitha/AQG_CV_Squad") model = AutoModelForQuestionAnswering.from_pretrained("sunitha/AQG_CV_Squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from sunitha/AQG_CV_Squad: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/sunitha/AQG_CV_Squad/resolve/main/training_args.bin
- Command line
-
hf download hf://sunitha/AQG_CV_Squad/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/sunitha/AQG_CV_Squad/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- d3427f424ffbad8de34f359898b76b1eefa6ca96228b734f0ca824aecba4a334
- Size of remote file:
- 3.06 kB
- SHA256:
- 9965e0a9ad8945e97fea0675859c864940be6c3bdc07b90a2b631624b5965d46
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