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| title: Bio Protocol | |
| emoji: 🧬 | |
| colorFrom: pink | |
| colorTo: purple | |
| sdk: static | |
| pinned: true | |
| license: mit | |
| short_description: Your Gateway Drug to Decentralized Science. | |
| # Bio Protocol | |
| Welcome to **Bio Protocol** 🧬, your gateway drug to decentralized science. We're pioneering the intersection of AI, biotechnology, and blockchain to democratize scientific research and innovation. | |
| ## About Us | |
| At Bio Protocol, we're a team of AI engineers and researchers dedicated to building open-source tools that accelerate decentralized science. Our work focuses on leveraging advanced AI techniques to make scientific data more accessible, verifiable, and collaborative. We blend cutting-edge machine learning with blockchain principles to create transparent, reproducible pipelines for research. | |
| Our mission is to empower scientists, developers, and enthusiasts worldwide to contribute to a decentralized ecosystem where knowledge isn't siloed but shared freely under open licenses like MIT. | |
| ## Our Projects | |
| We specialize in AI-driven solutions for scientific workflows. Here are some of our key initiatives: | |
| - **RAG Pipelines**: Implementing retrieval-augmented generation (RAG) systems inspired by OpenScholar to enhance knowledge retrieval from vast scientific literature. These pipelines enable efficient querying and synthesis of research data. | |
| - **LLM Training**: Fine-tuning and training large language models (LLMs) tailored for biotech applications, such as analyzing genetic sequences, predicting protein structures, or automating literature reviews. | |
| - **PDF Miner ML Models**: Developing machine learning models for extracting structured data from scientific PDFs. These tools help parse complex documents, extract tables, figures, and text, making them machine-readable for downstream AI tasks. | |
| Explore our repositories on Hugging Face for models, datasets, and code you can use or contribute to. | |