Instructions to use Docty/question_and_answer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Docty/question_and_answer 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="Docty/question_and_answer")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Docty/question_and_answer") model = AutoModelForQuestionAnswering.from_pretrained("Docty/question_and_answer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from Docty/question_and_answer: direct link, hf CLI and curl.
- Browser
- Download file 261 MB
-
https://huggingface.co/Docty/question_and_answer/resolve/main/tf_model.h5
- Command line
-
hf download hf://Docty/question_and_answer/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/Docty/question_and_answer/resolve/main/tf_model.h5
261 MB
- Xet hash:
- fd384b7bf0eee5be0ecfa5d081003934e678e4e5bbce6950fb49810786af0746
- Size of remote file:
- 261 MB
- SHA256:
- 0e28afe23658cb018f3507106a07f29025ace312df02a44059a4162eed29847f
路
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