Dolphin3.0-Qwen2.5-0.5B is a 0.5 billion parameter instruct-tuned language model from the Dolphin 3.0 series, curated and trained by Eric Hartford, Ben Gitter, BlouseJury, and Cognitive Computations. Built on the Qwen 2.5 architecture, it is designed as a general-purpose local model for coding, math, agentic tasks, function calling, and general conversational use cases. This model emphasizes user control over system prompts and alignment, offering an alternative to proprietary models by allowing full customization of behavior and data privacy.
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