📚 BigLAM: Machine Learning for Libraries, Archives, and Museums

BigLAM is a community-driven initiative to build an open ecosystem of machine learning models, datasets, and tools for Libraries, Archives, and Museums (LAMs).

We aim to:

• 🗃️ Share machine-learning-ready datasets from LAMs via the Hugging Face Hub
• 🤖 Train and release open-source models for LAM-relevant tasks
• 🛠️ Develop tools and approaches tailored to LAM use cases

🌍 Why It Matters

Cultural heritage data is often underrepresented in machine learning. BigLAM helps address this by:

• Supporting inclusive and responsible AI
• Helping institutions experiment with ML for access, discovery, and preservation
• Ensuring that ML systems reflect diverse human knowledge and expression
• Developing tools and methods that work well with the unique formats, values, and needs of LAMs