From a766b70a8fd19775c8ef0053242e7bbd721d07b4 Mon Sep 17 00:00:00 2001 From: Vladimir Blagojevic Date: Wed, 6 Jul 2022 16:51:09 +0200 Subject: [PATCH] Tutorial 18:Open in Colab doesn't work in Firefox (#2767) * 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> --- docs/_src/tutorials/tutorials/18.md | 3 ++- tutorials/Tutorial18_GPL.ipynb | 3 ++- 2 files changed, 4 insertions(+), 2 deletions(-) diff --git a/docs/_src/tutorials/tutorials/18.md b/docs/_src/tutorials/tutorials/18.md index 47605b7f2..a3703c5bb 100644 --- a/docs/_src/tutorials/tutorials/18.md +++ b/docs/_src/tutorials/tutorials/18.md @@ -8,9 +8,10 @@ id: "tutorial18md" ---> # 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) -#### 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. diff --git a/tutorials/Tutorial18_GPL.ipynb b/tutorials/Tutorial18_GPL.ipynb index 9634dca7f..843b89431 100644 --- a/tutorials/Tutorial18_GPL.ipynb +++ b/tutorials/Tutorial18_GPL.ipynb @@ -4,9 +4,10 @@ "cell_type": "markdown", "source": [ "# 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", "\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", "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",