ludwig and OpenLLM

These are complements: Ludwig provides the low-code framework for building and training custom models, while OpenLLM handles deployment and serving those models (or other open-source LLMs) as production API endpoints.

ludwig
77
Verified
OpenLLM
63
Established
Maintenance 22/25
Adoption 10/25
Maturity 25/25
Community 20/25
Maintenance 10/25
Adoption 10/25
Maturity 25/25
Community 18/25
Stars: 11,657
Forks: 1,212
Downloads:
Commits (30d): 55
Language: Python
License: Apache-2.0
Stars: 12,161
Forks: 803
Downloads:
Commits (30d): 0
Language: Python
License: Apache-2.0
No risk flags
No risk flags

About ludwig

ludwig-ai/ludwig

Low-code framework for building custom LLMs, neural networks, and other AI models

This tool helps machine learning engineers and data scientists build custom AI models, including large language models (LLMs) and deep neural networks, with minimal coding. You provide your dataset and a simple configuration file, and Ludwig outputs a trained, production-ready AI model. It's designed for practitioners who need to quickly develop and deploy advanced AI solutions without deep diving into complex code.

AI model training natural language processing deep learning predictive analytics LLM fine-tuning

About OpenLLM

bentoml/OpenLLM

Run any open-source LLMs, such as DeepSeek and Llama, as OpenAI compatible API endpoint in the cloud.

This project helps software developers, machine learning engineers, and data scientists easily host and serve open-source Large Language Models (LLMs) from their own cloud infrastructure. It takes various open-source LLMs as input and outputs an OpenAI-compatible API endpoint, making it straightforward to integrate these models into applications. The primary users are developers building AI-powered applications who need to deploy and manage LLMs.

LLM deployment AI application development machine learning operations cloud infrastructure API development

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