Instructions to use TranVanTri352/MCQ_Paragraph_AI_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TranVanTri352/MCQ_Paragraph_AI_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="TranVanTri352/MCQ_Paragraph_AI_Model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("TranVanTri352/MCQ_Paragraph_AI_Model") model = AutoModelForSeq2SeqLM.from_pretrained("TranVanTri352/MCQ_Paragraph_AI_Model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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license: apache-2.0
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datasets:
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- rajpurkar/squad
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license: apache-2.0
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datasets:
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- rajpurkar/squad
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- ehovy/race
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- mandarjoshi/trivia_qa
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language:
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- vi
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- en
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library_name: transformers
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base_model:
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- google-t5/t5-small
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pipeline_tag: question-answering
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tags:
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- code
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