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Teams evaluating AI models, assistants and generative workflows, particularly container platforms and non-developers building without code — free to start, source available on GitHub.
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github.com
Ludwig
Low-code framework for building custom LLMs and deep neural networks. Declarative YAML configuration for training state-of-the-art models wi...
Checked Oct 27, 2026Evidence completeness: evidenceREADME refreshed Oct 16, 2026
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Low-code framework for building custom LLMs and deep neural networks. Declarative YAML configuration for training state-of-the-art models with PEFT/LoRA, 4-bit quantization, distributed training via Hugging Face Accelerate, and native Kubernetes support. Linux Foundation AI project. Apache 2.0 licensed.
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Teams evaluating AI models, assistants and generative workflows, particularly container platforms and non-developers building without code — free to start, source available on GitHub.
Known limitations
Workflows that require fully deterministic, auditable outputs with no human review step.
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Evidence summary
Known limitations
Workflows that require fully deterministic, auditable outputs with no human review step.
Catalogue confidence
Catalogue data checked Oct 27, 2026.
GitHub-backed record with source-attributed context.
Repository context
Fine-tune Llama-3.1 with LoRA in one config file
GitHub / ludwig-ai/ludwig
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