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| title: Experimentlab | |
| emoji: ⚛️ | |
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| <div align="center"> | |
| # ⚛️ Experimentlab (Experimentlab.in) | |
| ### Sovereign Artificial Intelligence for Science, Technology, Engineering & Mathematics (STEM) | |
| [](https://experimentlab.in) | |
| [-red?style=for-the-badge&logo=creativecommons&logoColor=white)](https://creativecommons.org/licenses/by-nc-sa/4.0/) | |
| [](https://github.com/Vigyan-workstation) | |
| [](https://huggingface.co/Experimentlab) | |
| [](https://discord.com/invite/Jck3tD6mhf) | |
| [](https://github.com/Vigyan-workstation/vigyan-workstation/releases/tag/v1.0.0) | |
| > *"Here’s to the rebels who build real things in the physical world. The ones who refuse to rent their intelligence by the token. Who pull the plug and keep calculating."* | |
| </div> | |
| --- | |
| ## 🌌 The Mission: Sovereign STEM Intelligence | |
| **Experimentlab** is a deep-tech research company building sovereign foundation models, efficient Small Language Models (SLMs), and air-gapped desktop workstations engineered specifically for **physical engineers, roboticists, semiconductor designers, and mathematicians**. | |
| Led by Founder & Chief Architect [Shreyansh Singh](https://github.com/shreyansh001boy-tech), our research bridges fundamental academic theory with sovereign edge execution: | |
| * **Zero Cloud Dependence**: 100% offline, privacy-first execution on local laptops and workstations. | |
| * **Deterministic Mathematical Truth**: Computer Algebra System (SymPy CAS) verification eliminating hallucinated calculus, ODEs, and physics. | |
| * **Sovereign Quantization**: Pioneering Sparse Mixture of Experts (MoE) and 1.58-bit ternary {-1, 0, +1} BitNet quantization running natively on edge CPUs and NPUs. | |
| --- | |
| ## 🏛️ The 5-Pillar Public AI Catalog | |
| ```mermaid | |
| graph LR | |
| A["Raw STEM Corpora (1B+ Tokens, arXiv, Dolma)"] --> B["Vigyan Sovereign Pretraining"] | |
| B --> C["1. Frontier STEM SLMs (32B / 7B / 2B)"] | |
| B --> D["2. Advanced Architectures (MoE / 1.58-bit / GRPO)"] | |
| B --> E["3. Domain Mastery (RTL / Math / Biomed / Vidhi)"] | |
| C --> F["5. Edge GGUF Runtimes & Desktop Studios"] | |
| D --> F | |
| E --> F | |
| B --> G["4. Foundation Pretraining Datasets"] | |
| ``` | |
| ### 1. 🚀 Frontier STEM & Dense SLMs | |
| * **[`Vigyan-AI-32B`](https://huggingface.co/Experimentlab/Vigyan-AI-32B)** & **[`Vigyan-AI-32B-Titan-v1`](https://huggingface.co/Experimentlab/Vigyan-AI-32B-Titan-v1)**: Flagship 32B Titan models for deep multi-step scientific deduction. | |
| * **[`Vigyan-7B-STEM-Instruct-v1`](https://huggingface.co/Experimentlab/Vigyan-7B-STEM-Instruct-v1)** & **[`Shreyansh-STEM-AI-7B-Final`](https://huggingface.co/Experimentlab/Shreyansh-STEM-AI-7B-Final)**: High-performance 7B dense scientific models. | |
| * **[`Shreyansh-STEM-AI-2B-v3`](https://huggingface.co/Experimentlab/Shreyansh-STEM-AI-2B-v3)** *(1,195+ downloads)* & **[`Shreyansh-STEM-AI-2B-v3-Distilled`](https://huggingface.co/Experimentlab/Shreyansh-STEM-AI-2B-v3-Distilled)**: Compact, battery-friendly edge SLMs. | |
| ### 2. 🌟 Advanced Architectures (MoE, 1.58-Bit Ternary, GRPO) | |
| * **[`Vigyan-1.5B-4x-MoE`](https://huggingface.co/Experimentlab/Vigyan-1.5B-4x-MoE)** *(1,669+ downloads)*: 4-expert routed Sparse MoE delivering 7B-class STEM reasoning at 1.5B inference latency. | |
| * **[`Vigyan-3B-4x-MoE`](https://huggingface.co/shreyansh12183/Vigyan-3B-4x-MoE)** *(704+ downloads)*: Advanced Top-1 routing multi-expert model tuned for symbolic logic. | |
| * **[`vigyan-3b-1.58bit-qat`](https://huggingface.co/shreyansh12183/vigyan-3b-1.58bit-qat)**: Pure 1.58-bit {-1, 0, +1} ternary BitNet model trained via Quantization-Aware Training (QAT). Replaces matrix multiplication with integer additions. | |
| * **[`vigyan-2b-reasoning-grpo`](https://huggingface.co/shreyansh12183/vigyan-2b-reasoning-grpo)**: DeepSeek-style GRPO test-time reasoning SLM trained on mathematical and logical verification trees. | |
| * **[`vigyan-olmoe-1b-7b-masterpiece-adapter`](https://huggingface.co/shreyansh12183/vigyan-olmoe-1b-7b-masterpiece-adapter)**: Ai2 OLMoE sparse expert architecture. | |
| ### 3. 🔬 Doctoral & Domain-Specialized Intelligence | |
| * **[`olmo2-7b-silicon-rtl-eda`](https://huggingface.co/Experimentlab/olmo2-7b-silicon-rtl-eda)**: Hardware silicon EDA specialist for synthesizable IEEE 1364 Verilog RTL, FSMs, and synchronous timing circuits. | |
| * **[`olmo2-7b-phd-pure-math`](https://huggingface.co/Experimentlab/olmo2-7b-phd-pure-math)**: Specialization in pure mathematics, formal topological proofs, and abstract algebra. | |
| * **[`olmo2-7b-biomed-chem`](https://huggingface.co/Experimentlab/olmo2-7b-biomed-chem)**: Deep biochemistry, enzyme kinetics, and molecular thermodynamics. | |
| * **[`olmo2-7b-astro-logic`](https://huggingface.co/Experimentlab/olmo2-7b-astro-logic)**: Orbital mechanics, Hohmann transfers, and astrophysical physics. | |
| * **[`Vidhi-AI-Instruct`](https://huggingface.co/Experimentlab/Vidhi-AI-Instruct)**: Sovereign Indian legal intelligence aligned with the Bharatiya Nyaya Sanhita (BNS). | |
| ### 4. 📚 Foundational Pretraining Corpora & Datasets | |
| * **[`shreyansh-1B-SLM-pretrain-stem-english`](https://huggingface.co/datasets/shreyansh12183/shreyansh-1B-SLM-pretrain-stem-english)**: 1 Billion token foundation pretraining corpus balanced for cold-start STEM intelligence. | |
| * **[`shreyansh-hinglish-english-stem-500k`](https://huggingface.co/datasets/shreyansh12183/shreyansh-hinglish-english-stem-500k)**: 500,000 sample bilingual Hinglish-English dataset tailored for Indian engineering students. | |
| * **[`vigyan-ai-research-papers`](https://huggingface.co/datasets/Experimentlab/vigyan-ai-research-papers)**: Curated corpus of scientific literature and verified technical preprints. | |
| ### 5. ⚡ Edge GGUF Runtimes & Workstation Integration | |
| * **[`Vigyan-Models-GGUF`](https://huggingface.co/Experimentlab/Vigyan-Models-GGUF)**: Quantized GGUF binaries (`Q4_K_M`) engineered for local execution via llama.cpp and Ollama. | |
| * **[`vigyan-7b-moe-gguf`](https://huggingface.co/shreyansh12183/vigyan-7b-moe-gguf)**: Edge quantized MoE binary. | |
| * **[Vigyan Workstation](https://github.com/Vigyan-workstation/vigyan-workstation)**: Open-source desktop engineering studio pairing these weights with 3D robotics kinematics, WaveDrom waveforms, and KiCad PCB netlists. | |
| --- | |
| ## ⚖️ Intellectual Property & Strict Non-Commercial Licensing | |
| All open-source models, benchmark suites, pretraining datasets, research whitepapers, and software released across the Vigyan / ExperimentLab ecosystem are strictly governed by the **Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)** license and the **ExperimentLab Sovereign Community & Demilitarized License**: | |
| * **Academic, Educational & Personal Research Use Only**: Freely permitted for students, academic researchers, university coursework, self-hosting, and civilian scientific inquiry. | |
| * **Strictly Non-Commercial Prohibition**: You may not sell, monetize, host as a paid API/SaaS wrapper, bundle with commercial hardware, or use for commercial advantage without prior written enterprise authorization from ExperimentLab AI. | |
| * **Demilitarized Civilian STEM Restriction**: Strictly prohibited for military, defense, weapons research, autonomous combat, or surveillance systems. | |
| * **Commercial Enterprise Licensing**: For commercial licensing, enterprise deployment, or institutional partnerships, contact [contact@experimentlab.in](mailto:contact@experimentlab.in). | |
| --- | |
| ## 📜 Academic Attribution & Sovereign Citation | |
| ```bibtex | |
| @article{singh2026vigyan, | |
| title={Vigyan Sovereign Trilogy: Empirical Scaling Laws and Deterministic Symbolic-AST Evaluation of Edge Small Language Models}, | |
| author={Singh, Shreyansh}, | |
| institution={Vigyan AI Open Research}, | |
| journal={Vigyan AI Research Publications}, | |
| year={2026}, | |
| url={https://github.com/shreyansh001boy-tech/vigyan-sovereign-benchmark} | |
| } | |
| ``` | |
| --- | |
| <div align="center"> | |
| <sub>Crafted with passion for sovereign open-source STEM research by <a href="https://experimentlab.in">ExperimentLab.in</a> • Built for the Crazy Ones.</sub> | |
| </div> | |