Ludwig
Low-code framework for building custom AI models by Predibase.
About
Ludwig by Predibase is a declarative deep learning framework that lets you train, fine-tune, and deploy models from a YAML configuration with no boilerplate Python. It covers LLM fine-tuning, multimodal models, and tabular tasks, builds on PyTorch, Transformers, and Ray, and scales from a laptop to a distributed cluster. It targets users who want custom models without writing training loops. Released under the Apache 2.0 license.
Reviews (0)
Leave a Review
No reviews yet. Be the first to review!
Details
- Category
- Model Training & Fine-Tuning
- Price
- Free
- Platform
- Local/Desktop
- Difficulty
- Easy (2/5)
- License
- Apache-2.0
- Minimum VRAM
- 8 GB
- Added
- Apr 3, 2026
Related Tools
Training scripts for Stable Diffusion fine-tuning with LoRA and DreamBooth.
No-code tool by Hugging Face for training ML models automatically.
All-in-one Stable Diffusion fine-tuning tool with intuitive GUI.
Parameter-efficient fine-tuning technique that adapts large models with minimal trainable parameters.
Library for post-training foundation models with SFT, DPO, GRPO, and other RL methods.
Efficient LLM quantization preserving important weight channels.