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%2F1/pytorch_model.bin
- Command line
-
hf download hf://Hansollll/qa_model@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Hansollll/qa_model/resolve/refs%2Fpr%2F1/pytorch_model.bin
265 MB
- Xet hash:
- f8f27c079afa783e38794188160e643d138ca7724c17a5979a0c2765705a6baa
- Size of remote file:
- 265 MB
- SHA256:
- 0314978ed7697bcf7a8f9e65c664c55f11996bffea8847cdfad4275acef501a4
路
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