Ludwig Alternatives
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.
Explore 20 alternatives to Ludwig across 1 category. Each tool listed below shares at least one category with Ludwig.
Top Ludwig alternatives at a glance
- Amazon Bedrock. Managed API access to foundation models on AWS with built-in fine-tuning and agent tooling
- Anyscale. Fast, cost-efficient, serverless APIs for LLM Serving and Fine Tuning
- Axolotl. Open-source toolkit for fine-tuning LLMs with a single YAML config across the full training pipeline
- fal. Build the next generation of creativity with fal. Lightning fast inference.
- FinetuneDB. Capture production data, evaluate outputs collaboratively, and fine-tune your LLM's performance
🧠 Fine-tuning
LLaMA-Factory
Open-source fine-tuning framework for 100+ LLMs with a web UI
Open Source
Free Trial
torchtune
PyTorch-native library for fine-tuning LLMs on consumer and enterprise GPUs
Open Source
Free Trial
TRL
Hugging Face library for training language models with RLHF, SFT, and DPO
Open Source
Free Trial
Unsloth
Fine-tune LLMs up to 30x faster with 90% less memory usage
Open Source
Free Trial
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