Instructions to use stefandi/test_qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use stefandi/test_qa_model 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="stefandi/test_qa_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("stefandi/test_qa_model") model = AutoModelForQuestionAnswering.from_pretrained("stefandi/test_qa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from stefandi/test_qa_model: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/stefandi/test_qa_model/resolve/main/training_args.bin
- Command line
-
hf download hf://stefandi/test_qa_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/stefandi/test_qa_model/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- b6e3a302951a0c228f96edeaaef7dab44a292eee3245518ef29850f0808f1d0b
- Size of remote file:
- 4.98 kB
- SHA256:
- 292dd7dabc752c21cac5d14ed33250ae61c7e204568c4a6d3119705dbae9d824
路
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