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Just tested Argilla's new data annotation feature - it's a game changer for AI project quality. 
Just tested Argilla's new data annotation feature - it's a game changer for AI project quality. 
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Upload CSVs, work with published datasets, or improve existing ones directly on HuggingFace Hub. Setup took < 2 minutes, no code needed (see example below where I selected a dataset to classify tweets in categories).
Upload CSVs, work with published datasets, or improve existing ones directly on HuggingFace Hub. Setup took < 2 minutes, no code needed (see example below where I selected a dataset to classify tweets in categories).
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Real world impact: Missing in Chicago won a Pulitzer using a similar approach - 200 volunteers labeled police misconduct files to train their model. That's the power of good data annotation.
Real world impact: Missing in Chicago won a Pulitzer using a similar approach - 200 volunteers labeled police misconduct files to train their model. That's the power of good data annotation.
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Three immediate use cases I see:
Three immediate use cases I see:
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- Build collaborative training sets with your community (surprisingly underused in AI journalism)
- Build collaborative training sets with your community (surprisingly underused in AI journalism)
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- Turn your website chatbot logs into high-quality fine-tuning data
- Turn your website chatbot logs into high-quality fine-tuning data
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- Compare generated vs published content (great for SEO headlines)
- Compare generated vs published content (great for SEO headlines)
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Works for solo projects or teams up to 100 people. All integrated with HuggingFace Hub for immediate model training.
Works for solo projects or teams up to 100 people. All integrated with HuggingFace Hub for immediate model training.
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Interesting to see tools like this making data quality more accessible. Data quality is the hidden driver of AI success that we don't talk about enough.
Interesting to see tools like this making data quality more accessible. Data quality is the hidden driver of AI success that we don't talk about enough.
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- Check out the blogpost: 
- Check out the blogpost: 
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https://huggingface.co/blog/argilla-ui-hub
https://huggingface.co/blog/argilla-ui-hub
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- And the quickstart guide: 
- And the quickstart guide: 
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https://docs.argilla.io/latest/getting_started/quickstart/
https://docs.argilla.io/latest/getting_started/quickstart/
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Just tested Argilla's new data annotation feature - it's a game changer for AI project quality. 

Upload CSVs, work with published datasets, or improve existing ones directly on HuggingFace Hub. Setup took < 2 minutes, no code needed (see example below where I selected a dataset to classify tweets in categories).

Real world impact: Missing in Chicago won a Pulitzer using a similar approach - 200 volunteers labeled police misconduct files to train their model. That's the power of good data annotation.

Three immediate use cases I see:
- Build collaborative training sets with your community (surprisingly underused in AI journalism)
- Turn your website chatbot logs into high-quality fine-tuning data
- Compare generated vs published content (great for SEO headlines)

Works for solo projects or teams up to 100 people. All integrated with HuggingFace Hub for immediate model training.

Interesting to see tools like this making data quality more accessible. Data quality is the hidden driver of AI success that we don't talk about enough.

- Check out the blogpost: https://huggingface.co/blog/argilla-ui-hub
- And the quickstart guide: https://docs.argilla.io/latest/getting_started/quickstart/


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