Instructions to use rooftopcoder/bert-base-uncased-coqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rooftopcoder/bert-base-uncased-coqa 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="rooftopcoder/bert-base-uncased-coqa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("rooftopcoder/bert-base-uncased-coqa") model = AutoModelForQuestionAnswering.from_pretrained("rooftopcoder/bert-base-uncased-coqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from rooftopcoder/bert-base-uncased-coqa: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/rooftopcoder/bert-base-uncased-coqa/resolve/d07676d733d1be56e85e5fa3ed7b3fb78625cc36/training_args.bin
- Command line
-
hf download hf://rooftopcoder/bert-base-uncased-coqa@d07676d733d1be56e85e5fa3ed7b3fb78625cc36/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rooftopcoder/bert-base-uncased-coqa/resolve/d07676d733d1be56e85e5fa3ed7b3fb78625cc36/training_args.bin
3.96 kB
- Xet hash:
- 37f46b0e155a5ee65e8da0baf7404e3cfef3c010ec87828a59d5cbfd262ea6f9
- Size of remote file:
- 3.96 kB
- SHA256:
- 6e1be30832b6775939072b467b5767bc1c8cc25eaada455b855a136d1347c817
路
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