Instructions to use jtatman/question_generation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jtatman/question_generation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("jtatman/question_generation") model = AutoModelForSeq2SeqLM.from_pretrained("jtatman/question_generation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from jtatman/question_generation: direct link, hf CLI and curl.
- Browser
- Download file 561 Bytes
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https://huggingface.co/jtatman/question_generation/resolve/main/README.md
- Command line
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hf download hf://jtatman/question_generation/README.md
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curl -L -o README.md https://huggingface.co/jtatman/question_generation/resolve/main/README.md
561 Bytes
| library_name: transformers | |
| tags: | |
| - bart | |
| - question/answer | |
| - question generation | |
| license: apache-2.0 | |
| # Model Card for Model ID | |
| This is a merge of a lora adapter [mou3az/Question-Generation](https://huggingface.co/mou3az/Question-Generation) with the base model [facebook/bart-base](https://huggingface.co/facebook/bart-base). | |
| There have been recent updates to the lora model - I strongly encourage you to look there for an improved version. | |
| All credits go to [mou3az](https://huggingface.co/mou3az). I just needed a merged model for my own purposes. |