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In a Training Loop ๐Ÿ”„
4

XCurOS

XCurOS

AI & ML interests

๐Ÿš€ Core Technical Interests LLM Optimization & Quantization: Focus on making large models run efficiently on consumer hardware (GGUF, AWQ, EXL2). Efficient Fine-Tuning (PEFT): Specialized in LoRA and QLoRA techniques for domain-specific adaptation. Model Evaluation Frameworks: Building robust pipelines to measure LLM performance beyond basic benchmarks. On-Device AI: Deploying high-performance models for edge computing and local environments. ๐Ÿ“ˆ Specialized Domains Algorithmic Trading & Time-Series: Applying Transformers and GRUs to financial markets and predictive signaling. Agentic Workflows: Designing autonomous AI agents that can navigate complex multi-step tasks. MLOps & Scalable Infrastructure: Optimizing Dockerized environments for seamless model serving and CI/CD. โœจ Minimalist "Bio" Style If you prefer a clean, "Next.js-style" aesthetic for your profile, try a bulleted list with emojis: โšก High-Performance Inference (A100/H100 Optimization) ๐Ÿง  Fine-Tuning 8B+ Models (Llama, Mistral, XCurOS) ๐ŸŒ Full-Stack AI Integration (Next.js + FastAPI + Docker) ๐Ÿ“Š Neural Time-Series Analysis

Recent Activity

liked a dataset 8 days ago
nohurry/Opus-4.6-Reasoning-3000x-filtered
updated a model 8 days ago
XCurOS/XCurOS-0.1-8B-Instruct
updated a Space 8 days ago
x-curos/README
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