Ludwig
Declarative deep learning framework for building and fine-tuning models with YAML configuration
Ludwig is a declarative, low-code framework for building, training, and fine-tuning AI models using YAML configuration instead of writing training code. Originally created at Uber AI, it is now maintained under the Linux Foundation. Supports LLM fine-tuning with QLoRA, LoRA, and other parameter-efficient methods. Handles multi-modal inputs (tabular, text, images, audio), distributed training via DDP and DeepSpeed, and larger-than-memory datasets. Works with models like Llama, Mistral, Mixtral, and Gemma.
Pricing: Free
Ludwig Alternatives
Explore 20 products in the Fine-tuning category. View all Ludwig alternatives.
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