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README.md

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+title: DarkUnitLab
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+# DarkUnitLab
+
+Research and engineering for reliable, efficient AI systems.
+
+We focus on the path from model experimentation to practical deployment:
+training, evaluation, quantization, inference, and the systems that connect them.
+
+## Focus Areas
+
+- **Model Training and Adaptation**
+  Parameter-efficient fine-tuning, data preparation, reproducible experiments,
+  and language and speech model adaptation.
+
+- **Inference and AI Infrastructure**
+  Quantization, model serving, runtime compatibility, and deployment across
+  GPUs and Ascend NPUs.
+
+- **Multimodal Intelligence**
+  Vision-language models, video understanding, evidence-grounded reasoning,
+  and retrieval-augmented generation.
+
+- **Language and Speech**
+  Cantonese and multilingual language modeling, automatic speech recognition,
+  and evaluations that reflect real-world usage.
+
+## Research Practices
+
+We aim to make experimental results inspectable and reproducible through:
+
+- Clear model provenance and attribution to upstream work.
+- Documented evaluation settings, limitations, and failure cases.
+- Explicit distinctions between research prototypes and validated releases.
+- Repository-specific documentation of hardware and runtime requirements.
+
+## Resources
+
+This organization hosts selected research and engineering artifacts.
+
+[Models](https://huggingface.co/models?author=DarkUnitLab) ·
+[Datasets](https://huggingface.co/datasets?author=DarkUnitLab) ·
+[Spaces](https://huggingface.co/spaces?search=DarkUnitLab)
+
+Please consult individual repository cards for availability, access conditions,
+licensing, and intended use.