Instructions to use Hansollll/qa_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hansollll/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="Hansollll/qa_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Hansollll/qa_model") model = AutoModelForQuestionAnswering.from_pretrained("Hansollll/qa_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Hansollll/qa_model: direct link, hf CLI and curl.
- Browser
- Download file 265 MB
-
https://huggingface.co/Hansollll/qa_model/resolve/refs%2Fpr%2F2/pytorch_model.bin
- Command line
-
hf download hf://Hansollll/qa_model@refs/pr/2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Hansollll/qa_model/resolve/refs%2Fpr%2F2/pytorch_model.bin
265 MB
- Xet hash:
- 5464a47ea55bb3e2e150bd0b7ced5202c1076391f82fd0bb7c61bb3e986be6e4
- Size of remote file:
- 265 MB
- SHA256:
- 2471161693c666427fa14bdc71941fd1b3a80376a1f8944b9c3dcec16bf761ab
路
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