cajal

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📝 Proposal: Add CAJAL — Local Scientific Paper Generation Model (4B-9B, Ranked #3) Project: CAJAL — Cognitive Academic Journal Authoring Layer Why CAJAL Fits This List CAJAL is a local scientific paper generator that runs entirely on consumer hardware. It generates publication-ready research papers with real citations, peer-review scoring, and zero cloud dependency. Key Highlights 🏆 Ranked #3 on P2PCLAW scientific paper benchmark (beaten only by Claude Sonnet 4.6) 🧠 Local 9B model (CAJAL-9B v2) with multiple quantizations (Q4KM, Q6K, Q80, F16) 📄 7-section papers: Abstract → Introduction → Methods → Results → Discussion → Conclusion → References 🔗 Real citations from arXiv and CrossRef — no hallucinated references ⚖️ Tribunal scoring: 8-10 LLM judges evaluate each paper on 10 quality dimensions 🔌 100+ integrations: Ollama, LangChain, Jupyter, VS Code, LlamaIndex 💻 Consumer hardware: 4-18 GB VRAM depending on quantization Model Zoo (HuggingFace) | Model | Size | Quantization | VRAM | Link | |-------|------|--------------|------|------| | CAJAL-4B | 4B | Q4KM | 4 GB | HF | | CAJAL-9B v2 | 9B | Q4KM | 6 GB | HF | | CAJAL-9B v2 | 9B | Q80 | 10 GB | HF | | CAJAL-9B v2 | 9B | F16 | 18 GB | HF | Quick Start bash pip install cajal-p2pclaw ollama create cajal -f Modelfile python -c "from cajalp2pclaw import PaperGenerator; g=PaperGenerator(); print(g.generate('Your research topic'))" Author Francisco Angulo de Lafuente (Agnuxo1) — Independent researcher, 35 years trajectory ORCID: 0009-0001-1634-7063 Coauthors: Vladimir Veselov (MIET, Moscow), Seid Mehammed Abdu (Woldia University, Ethiopia), Nirmal Tej Kumar (UT Dallas) Would love to contribute to this list! Happy to open a PR if preferred.

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