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davanstrien
updated
a
dataset
about 4 hours ago
librarian-bot
updated
a
dataset
about 5 hours ago
Discussion tracking new models trained on argilla/distilabel-intel-orca-dpo-pairs
97
#36 opened 11 months ago
by
librarian-bot
Discussion tracking new models trained on Open-Orca/OpenOrca
246
#19 opened about 1 year ago
by
librarian-bot
Discussion tracking new models trained on google/fleurs
176
#6 opened over 1 year ago
by
librarian-bot
Discussion tracking new models trained on LDJnr/Capybara
226
#33 opened 12 months ago
by
librarian-bot
Discussion tracking new models trained on OpenAssistant/oasst1
85
#7 opened over 1 year ago
by
librarian-bot
Discussion tracking new models trained on HuggingFaceH4/ultrafeedback_binarized
372
#37 opened 11 months ago
by
librarian-bot
Discussion tracking new models trained on HuggingFaceH4/ultrachat_200k
381
#15 opened about 1 year ago
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librarian-bot
Discussion tracking new models trained on argilla/ultrafeedback-binarized-preferences-cleaned
59
#43 opened 11 months ago
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librarian-bot
Discussion tracking new models trained on nvidia/HelpSteer
137
#21 opened about 1 year ago
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librarian-bot
davanstrien
updated
a
dataset
3 days ago
Discussion tracking new models trained on HuggingFaceH4/cai-conversation-harmless
27
#44 opened 11 months ago
by
librarian-bot
davanstrien
posted
an
update
6 days ago
Post
1532
Introducing FineWeb-C 🌐🎓, a community-built dataset for improving language models in ALL languages.
Inspired by FineWeb-Edu the community is labelling the educational quality of texts for many languages.
318 annotators, 32K+ annotations, 12 languages - and growing! 🌍
data-is-better-together/fineweb-c
Inspired by FineWeb-Edu the community is labelling the educational quality of texts for many languages.
318 annotators, 32K+ annotations, 12 languages - and growing! 🌍
data-is-better-together/fineweb-c
Discussion tracking new models trained on Muennighoff/natural-instructions
77
#32 opened about 1 year ago
by
librarian-bot
Post
2036
🇪🇺 Policy Thoughts in the EU AI Act Implementation 🇪🇺
There is a lot to like in the first draft of the EU GPAI Code of Practice, especially as regards transparency requirements. The Systemic Risks part, on the other hand, is concerning for both smaller developers and for external stakeholders.
I wrote more on this topic ahead of the next draft. TLDR: more attention to immediate large-scale risks and to collaborative solutions supported by evidence can help everyone - as long as developers disclose sufficient information about their design choices and deployment contexts.
Full blog here, based on our submitted response with @frimelle and @brunatrevelin :
https://huggingface.co/blog/yjernite/eu-draft-cop-risks#on-the-proposed-taxonomy-of-systemic-risks
There is a lot to like in the first draft of the EU GPAI Code of Practice, especially as regards transparency requirements. The Systemic Risks part, on the other hand, is concerning for both smaller developers and for external stakeholders.
I wrote more on this topic ahead of the next draft. TLDR: more attention to immediate large-scale risks and to collaborative solutions supported by evidence can help everyone - as long as developers disclose sufficient information about their design choices and deployment contexts.
Full blog here, based on our submitted response with @frimelle and @brunatrevelin :
https://huggingface.co/blog/yjernite/eu-draft-cop-risks#on-the-proposed-taxonomy-of-systemic-risks
- 2 replies
davanstrien
posted
an
update
27 days ago
Post
489
Increasingly, LLMs are becoming very useful for helping scale annotation tasks, i.e. labelling and filtering. When combined with the structured generation, this can be a very scalable way of doing some pre-annotation without requiring a large team of human annotators.
However, there are quite a few cases where it still doesn't work well. This is a nice paper looking at the limitations of LLM as an annotator for Low Resource Languages: On Limitations of LLM as Annotator for Low Resource Languages (2411.17637).
Humans will still have an important role in the loop to help improve models for all languages (and domains).
However, there are quite a few cases where it still doesn't work well. This is a nice paper looking at the limitations of LLM as an annotator for Low Resource Languages: On Limitations of LLM as Annotator for Low Resource Languages (2411.17637).
Humans will still have an important role in the loop to help improve models for all languages (and domains).
davanstrien
posted
an
update
30 days ago
Post
2472
First dataset for the new Hugging Face Bluesky community organisation:
bluesky-community/one-million-bluesky-posts 🦋
📊 1M public posts from Bluesky's firehose API
🔍 Includes text, metadata, and language predictions
🔬 Perfect to experiment with using ML for Bluesky 🤗
Excited to see people build more open tools for a more open social media platform!
📊 1M public posts from Bluesky's firehose API
🔍 Includes text, metadata, and language predictions
🔬 Perfect to experiment with using ML for Bluesky 🤗
Excited to see people build more open tools for a more open social media platform!
davanstrien
posted
an
update
about 1 month ago
Post
1348
The Bluesky AT Protocol unlocks exciting possibilities:
- Building custom feeds using ML
- Creating dashboards for data exploration
- Developing custom models for Bluesky
To gather Bluesky resources on the Hub, I've created a community org: https://huggingface.co/bluesky-community
My first rather modest contribution is a dashboard that shows the number of posts every second. Drinking straight from the firehose API 🚰
bluesky-community/bluesky-posts-over-time
- Building custom feeds using ML
- Creating dashboards for data exploration
- Developing custom models for Bluesky
To gather Bluesky resources on the Hub, I've created a community org: https://huggingface.co/bluesky-community
My first rather modest contribution is a dashboard that shows the number of posts every second. Drinking straight from the firehose API 🚰
bluesky-community/bluesky-posts-over-time
- 1 reply
davanstrien
posted
an
update
about 1 month ago
Post
1306
huggingface.co/DIBT is dead! Long live https://huggingface.co/data-is-better-together!
We're working on some very cool projects so we're doing a bit of tidying of the Data is Better Together Hub org 🤓