ludwig
Ludwig is a declarative framework that allows to create, train and distribute deep learning models using YAML-based configuration files. LLM supports a variety of AI tasks such as fine-tuning, multi-mode models, and table data classification. Python offers control over model architecture and educational processes by reducing the need to write code.
ludwig
100ludwig-ai · Local AI / Self-Hosted LLM
Common commercial products in this category: ChatGPT, Claude, Gemini
- You can fine-tune LLM models with the YAML configuration file.
- You can train classification and time series prediction models on table data.
- You can distribute trained models using Ray Serve or KServe.
- • NeutralHacker News
Ludwig, a code-free deep learning toolbox
“Your configuration file looks really good! Why did you stop pursuing it? To your points: * That may be true, but I think it also depends on the level of abstraction. Fon instance in Ludwig the encoder, although configurable, are pretty monolitic. It's a trade off with…”
- • NeutralHacker News
Ludwig, a code-free deep learning toolbox
“Text is just one of the possible types of features supported in Ludwig. For those features, no, you can train models on any language, with a couple little caveats: you can train both character based models and word level ones. For character ones you don't really need anything,…”