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doxiy
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reacted to
abhishek's
post with 👍
over 1 year ago
Post
Happy to announce, brand new, open-source Hugging Face Competitions platform 🚀 Now, create a machine learning competition for your friends, colleagues or the world for FREE* and host it on Hugging Face: the AI community building the future. Creating a competition requires only two steps:
pip install competitions, then run competitions create and create competition by answering a few questions 💥 Checkout the github repo: https://github.com/huggingface/competitions and docs: https://hf.co/docs/competitions
- 6 replies
reacted to
clem's
post with 🤯
over 1 year ago
Post
Is synthetic data the future of AI? 🔥🔥🔥
@HugoLaurencon @Leyo & @VictorSanh are introducing HuggingFaceM4/WebSight , a multimodal dataset featuring 823,000 pairs of synthetically generated HTML/CSS codes along with screenshots of the corresponding rendered websites to train GPT4-V-like models 🌐💻
While crafting their upcoming foundation vision language model, they faced the challenge of converting website screenshots into usable HTML/CSS codes. Most VLMs suck at this and there was no public dataset available for this specific task, so they decided to create their own.
They prompted existing LLMs to generate 823k HTML/CSS codes of very simple websites. Through supervised fine-tuning of a vision language model on WebSight, they were able to generate the code to reproduce a website component, given a screenshot.
You can explore the dataset here: HuggingFaceM4/WebSight
What do you think?
@HugoLaurencon @Leyo & @VictorSanh are introducing HuggingFaceM4/WebSight , a multimodal dataset featuring 823,000 pairs of synthetically generated HTML/CSS codes along with screenshots of the corresponding rendered websites to train GPT4-V-like models 🌐💻
While crafting their upcoming foundation vision language model, they faced the challenge of converting website screenshots into usable HTML/CSS codes. Most VLMs suck at this and there was no public dataset available for this specific task, so they decided to create their own.
They prompted existing LLMs to generate 823k HTML/CSS codes of very simple websites. Through supervised fine-tuning of a vision language model on WebSight, they were able to generate the code to reproduce a website component, given a screenshot.
You can explore the dataset here: HuggingFaceM4/WebSight
What do you think?
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- 12 replies