Instructions to use ModelTC/bart-base-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bart-base-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="ModelTC/bart-base-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ModelTC/bart-base-squad") model = AutoModelForQuestionAnswering.from_pretrained("ModelTC/bart-base-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ModelTC/bart-base-squad: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/ModelTC/bart-base-squad/resolve/main/training_args.bin
- Command line
-
hf download hf://ModelTC/bart-base-squad/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ModelTC/bart-base-squad/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- 9d5cb08a7be09fc2181a6a8e06da492939fec372a87d3522317c59c64b355057
- Size of remote file:
- 3.06 kB
- SHA256:
- 970eaa587156caf23ef2f702269e5ba0a19bf72d4577e39ad54533fffd6ed8bb
路
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