Deploy compute-efficient Small Language Models (SLMs) engineered for digital autonomy. Open-weights, efficient, and air-gapped.
Open-Weights Commons: SLMs fine-tuned on curated multilingual datasets.
Air-Gapped Deployment: Local inference for absolute data sovereignty.
Quality Data Pipelines: Custom training data generation and synthetic data augmentation.
Need a SLM tailored to your industry? Whether you're in finance, healthcare, legal, or any sector requiring domain-specific language understanding — we can build and deploy custom fine-tuned models for your use case.
Our expertise stays open-source where it benefits the community, while enterprise-grade capabilities and specialized deployments remain available via API for organizations that require dedicated support and custom training.
First iteration of our Serbian SLM pipeline — two-stage LoRA fine-tuning on Qwen 2.5 0.5B with continued pretraining on Serbian Wikipedia and instruction tuning, deployed for in-browser inference via GGUF.
Test VernoByte SLMs directly in your browser. All compute is executed locally via WebAssembly. No data is transferred to external servers.