Tagged "kdnuggets"
8 articles tagged kdnuggets, 4 April 2026 to 22 July 2026. Newest first.
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Run the Mythos Enhanced Coding Model Locally with llama.cpp and Pi
A new guide demonstrates how to deploy the Mythos Enhanced Coding Model locally using llama.cpp and Raspberry Pi, making advanced code generation accessible on edge devices.
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7 Python Frameworks for Orchestrating Local AI Agents
KDnuggets publishes a comprehensive overview of Python frameworks for building and orchestrating AI agents that run locally. The guide covers frameworks that enable autonomous agent development without cloud dependencies, critical for privacy-sensitive and latency-critical applications.
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Running OpenClaw with Ollama: Practical Guide to Local LLM Deployment
KDnuggets published a practical guide demonstrating how to run OpenClaw models with Ollama, providing step-by-step instructions for developers seeking to deploy specialized models locally.
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Pairing Claude Code With Local Models
KDnuggets explores integrating Claude Code with local LLMs, enabling hybrid workflows that combine cloud and on-device inference for development tasks.
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Tweaking Local Language Model Settings with Ollama
A practical guide to optimizing Ollama configurations for various hardware setups and use cases, helping practitioners maximize inference performance on local systems.
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Self-Hosted LLMs in Production: Real-World Limits and Practical Lessons
Deep dive into the operational challenges and workarounds for deploying LLMs in production environments, drawing on practical experience with self-hosted systems.
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Run Qwen3.5 on an Old Laptop: A Lightweight Local Agentic AI Setup Guide
KDnuggets publishes a practical guide demonstrating how to run Qwen3.5 with agentic AI capabilities on resource-constrained hardware, making advanced local inference accessible to resource-limited environments.
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5 Useful Docker Containers for Agentic Developers
KDnuggets has compiled a guide to Docker containers that support local LLM deployment and agentic AI development. These containerized solutions simplify setup, reproducibility, and scaling of inference workloads.