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README.md

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+---
+datasets:
+- squad
+tags:
+- question-generation
+- distilt5
+- distilt5-qg
+widget:
+- text: "generate question: <hl> 42 <hl> is the answer to life, the universe and everything. </s>"
+- text: "question: What is 42 context: 42 is the answer to life, the universe and everything. </s>"
+license: "MIT"
+---
+
+## DistilT5 for question-generation
+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.
+
+The model is distilled using the **No Teacher Distillation** method proposed by Huggingface, [here](https://github.com/huggingface/transformers/tree/master/examples/seq2seq#distilbart).
+
+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.
+
+| Name                                                                            | BLEU-4  | METEOR  | ROUGE-L | QA-EM  | QA-F1  |
+|---------------------------------------------------------------------------------|---------|---------|---------|--------|--------|
+| [distilt5-qg-hl-6-4](https://huggingface.co/valhalla/distilt5-qg-hl-6-4)        | 18.4141 | 24.8417 | 40.3435 | -      | -      |
+| [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 |
+| [distilt5-qg-hl-12-6](https://huggingface.co/valhalla/distilt5-qg-hl-12-6)      | 20.5275 | 26.5010 | 43.2676 | -      | -      |
+| [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 |
+
+
+You can play with the model using the inference API. Here's how you can use it
+
+For QG
+
+`generate question: <hl> 42 <hl> is the answer to life, the universe and everything.`
+
+For QA
+
+`question: What is 42 context: 42 is the answer to life, the universe and everything.`
+
+For more deatils see [this](https://github.com/patil-suraj/question_generation) repo.
+
+### Model in action 🚀
+
+You'll need to clone the [repo](https://github.com/patil-suraj/question_generation).
+
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/patil-suraj/question_generation/blob/master/question_generation.ipynb)
+
+
+```python3
+from pipelines import pipeline
+nlp = pipeline("multitask-qa-qg", model="valhalla/distilt5-qa-qg-hl-6-4")
+
+# to generate questions simply pass the text
+nlp("42 is the answer to life, the universe and everything.")
+=> [{'answer': '42', 'question': 'What is the answer to life?'}]
+
+# for qa pass a dict with "question" and "context"
+nlp({
+    "question": "What is 42 ?",
+    "context": "42 is the answer to life, the universe and everything."
+})
+=> 'the answer to life, the universe and everything'
+```