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--- |
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datasets: |
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- squad |
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tags: |
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- question-generation |
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- distilt5 |
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- distilt5-qg |
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widget: |
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- text: 'generate question: <hl> 42 <hl> is the answer to life, the universe and everything. |
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</s>' |
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- text: 'question: What is 42 context: 42 is the answer to life, the universe and |
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everything. </s>' |
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license: mit |
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--- |
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## DistilT5 for question-generation |
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This is distilled version of [t5-small-qa-qg-hl](https://huggingface.co/valhalla/t5-small-qa-qg-hl) model trained for question answering and answer aware question generation tasks. |
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The model is distilled using the **No Teacher Distillation** method proposed by Huggingface, [here](https://github.com/huggingface/transformers/tree/master/examples/seq2seq#distilbart). |
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We just copy alternating layers from `t5-small-qa-qg-hl` and finetune more on the same data. Following table lists other distilled models and their metrics. |
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| Name | BLEU-4 | METEOR | ROUGE-L | QA-EM | QA-F1 | |
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|---------------------------------------------------------------------------------|---------|---------|---------|--------|--------| |
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| [distilt5-qg-hl-6-4](https://huggingface.co/valhalla/distilt5-qg-hl-6-4) | 18.4141 | 24.8417 | 40.3435 | - | - | |
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| [distilt5-qa-qg-hl-6-4](https://huggingface.co/valhalla/distilt5-qa-qg-hl-6-4) | 18.6493 | 24.9685 | 40.5605 | 76.13 | 84.659 | |
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| [distilt5-qg-hl-12-6](https://huggingface.co/valhalla/distilt5-qg-hl-12-6) | 20.5275 | 26.5010 | 43.2676 | - | - | |
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| [distilt5-qa-qg-hl-12-6](https://huggingface.co/valhalla/distilt5-qa-qg-hl-12-6)| 20.6109 | 26.4533 | 43.0895 | 81.61 | 89.831 | |
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You can play with the model using the inference API. Here's how you can use it |
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For QG |
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`generate question: <hl> 42 <hl> is the answer to life, the universe and everything.` |
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For QA |
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`question: What is 42 context: 42 is the answer to life, the universe and everything.` |
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For more deatils see [this](https://github.com/patil-suraj/question_generation) repo. |
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### Model in action 🚀 |
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You'll need to clone the [repo](https://github.com/patil-suraj/question_generation). |
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[](https://colab.research.google.com/github/patil-suraj/question_generation/blob/master/question_generation.ipynb) |
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```python3 |
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from pipelines import pipeline |
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nlp = pipeline("multitask-qa-qg", model="valhalla/distilt5-qa-qg-hl-6-4") |
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# to generate questions simply pass the text |
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nlp("42 is the answer to life, the universe and everything.") |
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=> [{'answer': '42', 'question': 'What is the answer to life?'}] |
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# for qa pass a dict with "question" and "context" |
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nlp({ |
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"question": "What is 42 ?", |
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"context": "42 is the answer to life, the universe and everything." |
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}) |
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=> 'the answer to life, the universe and everything' |
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``` |
