Awesome-LLMOps and Awesome-LLM-Resources-List

Awesome-LLMOps
56
Established
Maintenance 10/25
Adoption 10/25
Maturity 16/25
Community 20/25
Maintenance 13/25
Adoption 10/25
Maturity 8/25
Community 21/25
Stars: 215
Forks: 40
Downloads:
Commits (30d): 0
Language: Python
License: Apache-2.0
Stars: 502
Forks: 84
Downloads:
Commits (30d): 9
Language: Python
License:
No Package No Dependents
No License No Package No Dependents

About Awesome-LLMOps

InftyAI/Awesome-LLMOps

🎉 An awesome & curated list of best LLMOps tools.

This is a curated list of tools for managing and deploying Large Language Models (LLMs) in a production environment. It helps engineers and machine learning practitioners find solutions for common tasks like running LLMs efficiently, orchestrating complex AI applications, and training or fine-tuning models. It takes in a need to implement an LLM-based solution and outputs a selection of suitable tools for different stages of the LLM lifecycle.

LLM deployment AI model operations Machine learning engineering AI application development Model scaling

About Awesome-LLM-Resources-List

ilsilfverskiold/Awesome-LLM-Resources-List

A Curated Collection of resources for applied AI engineering (work in progress).

This collection helps AI engineers and practitioners navigate the rapidly evolving landscape of Large Language Model (LLM) tools and platforms. It provides curated lists for hosting private or open-source LLMs, accessing off-the-shelf models via API, and performing local inference. The output is a clear overview of options, features, and pricing to help you make informed decisions for your projects.

AI engineering LLM deployment model hosting API integration machine learning operations

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