Instructions to use ModelTC/bert-base-squad2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ModelTC/bert-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="ModelTC/bert-base-squad2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("ModelTC/bert-base-squad2") model = AutoModelForQuestionAnswering.from_pretrained("ModelTC/bert-base-squad2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ModelTC/bert-base-squad2: direct link, hf CLI and curl.
- Browser
- Download file 3.12 kB
-
https://huggingface.co/ModelTC/bert-base-squad2/resolve/main/training_args.bin
- Command line
-
hf download hf://ModelTC/bert-base-squad2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ModelTC/bert-base-squad2/resolve/main/training_args.bin
3.12 kB
- Xet hash:
- b3556b3f40988f25b3b743b4b373185d1ddd7cc646a2fbe062dc4e2c521e60cb
- Size of remote file:
- 3.12 kB
- SHA256:
- 6876c600d758a6201e003081023b4b7311d17bd1887e875d7315cdd39d1a50e3
路
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