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Tutorial 18:Open in Colab doesn't work in Firefox (#2767)

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* Tutorial 18:Open in Colab doesn't work in Firefox

* Tutorial 18:Open in Colab doesn't work in Firefox v2

* Update Documentation & Code Style

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
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Vladimir Blagojevic 2022-07-06 16:51:09 +02:00 committed by GitHub
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docs/_src/tutorials/tutorials/18.md
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@ -8,9 +8,10 @@ id: "tutorial18md"
---> --->
# Generative Pseudo Labeling for Domain Adaptation of Dense Retrievals # Generative Pseudo Labeling for Domain Adaptation of Dense Retrievals
[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/deepset-ai/haystack/blob/master/tutorials/Tutorial18_GPL.ipynb) [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/deepset-ai/haystack/blob/master/tutorials/Tutorial18_GPL.ipynb)
#### Note: Adapted to Haystack from Nils Riemers' original [notebook](https://colab.research.google.com/gist/jamescalam/d2c888775c87f9882bb7c379a96adbc8/gpl-domain-adaptation.ipynb#scrollTo=183ff7ab) *Note: Adapted to Haystack from Nils Riemers' original [notebook](https://colab.research.google.com/gist/jamescalam/d2c888775c87f9882bb7c379a96adbc8/gpl-domain-adaptation.ipynb#scrollTo=183ff7ab)
The NLP models we use every day were trained on a corpus of data that reflects the world from the past. In the meantime, we've experienced world-changing events, like the COVID pandemics, and we'd like our models to know about them. Training a model from scratch is tedious work but what if we could just update the models with new data? Generative Pseudo Labeling comes to the rescue. The NLP models we use every day were trained on a corpus of data that reflects the world from the past. In the meantime, we've experienced world-changing events, like the COVID pandemics, and we'd like our models to know about them. Training a model from scratch is tedious work but what if we could just update the models with new data? Generative Pseudo Labeling comes to the rescue.

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tutorials/Tutorial18_GPL.ipynb
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"cell_type": "markdown", "cell_type": "markdown",
"source": [ "source": [
"# Generative Pseudo Labeling for Domain Adaptation of Dense Retrievals\n", "# Generative Pseudo Labeling for Domain Adaptation of Dense Retrievals\n",
"\n",
"[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/deepset-ai/haystack/blob/master/tutorials/Tutorial18_GPL.ipynb)\n", "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/deepset-ai/haystack/blob/master/tutorials/Tutorial18_GPL.ipynb)\n",
"\n", "\n",
"#### Note: Adapted to Haystack from Nils Riemers' original [notebook](https://colab.research.google.com/gist/jamescalam/d2c888775c87f9882bb7c379a96adbc8/gpl-domain-adaptation.ipynb#scrollTo=183ff7ab)\n", "*Note: Adapted to Haystack from Nils Riemers' original [notebook](https://colab.research.google.com/gist/jamescalam/d2c888775c87f9882bb7c379a96adbc8/gpl-domain-adaptation.ipynb#scrollTo=183ff7ab)\n",
"\n", "\n",
"The NLP models we use every day were trained on a corpus of data that reflects the world from the past. In the meantime, we've experienced world-changing events, like the COVID pandemics, and we'd like our models to know about them. Training a model from scratch is tedious work but what if we could just update the models with new data? Generative Pseudo Labeling comes to the rescue.\n", "The NLP models we use every day were trained on a corpus of data that reflects the world from the past. In the meantime, we've experienced world-changing events, like the COVID pandemics, and we'd like our models to know about them. Training a model from scratch is tedious work but what if we could just update the models with new data? Generative Pseudo Labeling comes to the rescue.\n",
"\n", "\n",