awesome-llm-productization
github.com/oscinis-com/awesome-llm-productization ↗Awesome-LLM-Productization: a curated list of tools/tricks/news/regulations about AI and Large Language Model (LLM) productization
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me llm monitoring resources from awesome-llm-productization"
Installation instructions →What's inside
Models and Tools
- AuditNLGLLM Monitoring
an open-source library that can help reduce the risks associated with using generative AI systems for language. The library supports three aspects of trust detection and improvement: Factualness, Safety, and Constraint.
- Awesome MLOpsGeneral MLOps Tools
A curated list of awesome MLOps tools
- ChatGLM-6BOpen LLM Models
an open bilingual language model based on General Language Model (GLM) framework, with 6.2 billion parameters. (Note from the repo: a small LM to start with so that you can have a taste on prompting & finetuning. You can use a comemrcial grade graphics card with only 8GB to successfully fine tune it without any other financial commitment. You can use it like it is a BERT.)
- ChromaDBVector Store
open-source embedding database (Python based - in-memory only at the moment)
- clip-as-serviceEmbeddings
a low-latency high-scalability service for embedding images and text. It can be easily integrated as a microservice into neural search solutions (Python based, Apache 2);
- dbtGeneral MLOps Tools
dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
Showing a sample of 50 resources. View the full list on GitHub →