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README.md
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<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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SNIP-IGEL has been fine-tuned on [instruct-snippet-mlsum](https://huggingface.co/datasets/snipaid/instruct-snippet-mlsum). MLSUM is a dataset containing a german subset with text, title and teaser for news articles from the newspaper "Süddeutsche Zeitung". The dataset has been augmented with snippet data generated using a composite prompt which involves generating a SERP, keywords and a tweet for the news articles using a student-teacher-approach. Also see [snippet-mlsum-500](https://huggingface.co/datasets/snipaid/snippet-mlsum-500) for the dataset without instructions and our [blogpost](https://snipaid-nlg.github.io/2023/04/13/SNIP-IGEL.html) for more information about the construction of the dataset.
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<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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SNIP-IGEL has been fine-tuned on [instruct-snippet-mlsum](https://huggingface.co/datasets/snipaid/instruct-snippet-mlsum). MLSUM is a dataset containing a german subset with text, title and teaser for news articles from the newspaper "Süddeutsche Zeitung". The dataset has been augmented with snippet data generated using a composite prompt which involves generating a SERP, keywords and a tweet for the news articles using a student-teacher-approach. Also see [snippet-mlsum-500](https://huggingface.co/datasets/snipaid/snippet-mlsum-500) for the dataset without instructions and our [blogpost](https://snipaid-nlg.github.io/2023/04/13/SNIP-IGEL.html) for more information about the construction of the dataset.
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# Environmental Impact
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Carbon emissions were estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact/#compute) presented in Lacoste et al. (2019).
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Hardware Type: RTX 4090
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Hours used: 1h 50min 21s
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Cloud Provider: Vast.ai
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Compute Region: Poland
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Carbon Emitted: ~0.54 kg of CO2e
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