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title: README
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We are a community of researchers from different countries and institutions interested in studying the emerging open source AI ecosystem.
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Learn more about our areas of interest below and join us to uncover the activity and impact of different initiatives focused on openness in AI.
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<details>
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<summary><b
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- Using activity data from Hugging Face Hub datasets, models and spaces, we ran a three-part quantitative analysis of development activity, finding that:
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- Link to Paper: [The AI Community Building the Future? A Quantitative Analysis of Development Activity on Hugging Face Hub](https://huggingface.co/papers/2405.13058)
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</details>
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<summary><b
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- We are looking into what kinds of downstream activity are most prevalent for different kinds of foundation models.
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What kinds of derivations (e.g. fine tuning, quantizing) are most popular?
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<summary><b
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title: README
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emoji: 🖇️
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**This is a community of researchers from different countries and institutions interested in studying the emerging open-source AI ecosystem.**
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We believe that a diverse and inclusive community leads to more robust and impactful research in open-source AI. We welcome contributors with diverse backgrounds and skills.
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Learn more about our areas of interest below and join us to uncover the activity and impact of different initiatives focused on openness in AI.
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# Research Projects
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<details>
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<summary><b>✅ Quantitative Analysis of Hugging Face Hub</b></summary>
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- Using activity data from Hugging Face Hub datasets, models and spaces, we ran a three-part quantitative analysis of development activity, finding that:
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- activity is extremely imbalanced between repositories; with over 70% of models having 0 downloads, while 1% accounting for 99% of downloads
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- the community has a core-periphery structure, with a core of prolific developers while the large majority (89%) of developers are "islands", primarily working alone.
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- Link to Paper: [The AI Community Building the Future? A Quantitative Analysis of Development Activity on Hugging Face Hub](https://huggingface.co/papers/2405.13058)
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</details>
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<summary><b>🚧 Model Tree Lineages from Base Models to Derived Models</b> </summary>
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- We are looking into what kinds of downstream activity are most prevalent for different kinds of foundation models.
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What kinds of derivations (e.g. fine tuning, quantizing) are most popular?
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</details>
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<details open>
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<summary><b>🚧 Cartography of Collaboration in the Open Source AI Ecosystem</b> </summary>
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- We are investigating how open source AI artefacts such as open datasets and open-weight models are built and who contributes to this process across the model building pipeline, including during the pre-release and post-release phases.
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- Our research aims to map collaboration practices from pre-release to post-release across diverse organisational contexts,
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including individuals, grassroots initiatives, research institutes, startups, and large technology companies, and geographies.
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</details>
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# Open to collaboration!
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<div style="background: linear-gradient(to right, lightyellow, lightcoral); padding: 1px 20px; border-radius: 10px; margin-bottom: 20px; margin-top:20px; color:black;">
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<h2 style="color:black; padding: 0, margin:0">Interested in open-source AI research?</h2>
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<p>We welcome researchers at all levels of experience. Here's how to get involved:</p>
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<ul>
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<li><b>Discuss ideas:</b> Share your thoughts and connect with other researchers on our <a style="color:black" href="https://huggingface.co/spaces/OSAIResearchCommunity/README/discussions">community page</a>.</li>
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<li><b>Join the organization:</b> If you're actively working on projects related to open-source AI, we encourage you to join our organization.</li>
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</ul>
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</div>
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