awesome-production-machine-learning
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EthicalML
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
- [mlinfra](https://mlinfra.io/) aims to help users deploy mlops server side tools faster and in a standardised way. - It provides an easy convenient way to describe the infrastructure stack and...
Such as https://github.com/wookayin/gpustat, https://github.com/Syllo/nvtop, and https://github.com/XuehaiPan/nvitop. Any ideas?
Like https://github.com/facebookresearch/mmf, maybe we could create a new section named industry-strength multi-modality tools?
With the growing pace of Generative AI models and tools I am wondering whether there could be a space to add a section on Generative AI in this section. It...
Datasets like https://github.com/openai/human-eval, https://github.com/THUDM/AgentBench, https://github.com/the-crypt-keeper/can-ai-code, https://github.com/poloclub/diffusiondb, https://github.com/LAION-AI/CLIP_benchmark, https://github.com/carlini/yet-another-applied-llm-benchmark, https://github.com/EpistasisLab/pmlb and https://github.com/OpenBMB/UltraFeedback, https://github.com/defog-ai/sql-eval, https://github.com/OpenGenerativeAI/llm-colosseum, https://github.com/embeddings-benchmark/mteb are popular among ML practitioners, maybe we could create a new section named industry-strength datasets?
https://github.com/EthicalML/awesome-production-machine-learning/pull/406