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1.
▲
Numbers every LLM developer should know
github.com/ray-project
103 comments
3 years ago
richardliaw
428 points
2.
▲
A Comprehensive Guide for Building Rag-Based LLM Applications
github.com/ray-project
48 comments
3 years ago
robertnishihara
184 points
3.
▲
Aviary simplifies OSS LLM eval and deployment
github.com/ray-project
3 comments
3 years ago
waleedk
5 points
4.
▲
LLMPerf Leaderboard
github.com/ray-project
discuss
3 years ago
robertnishihara
5 points
5.
▲
LLM Inference Endpoint Performance Benchmarking Tool
github.com/ray-project
discuss
3 years ago
richardliaw
4 points
6.
▲
A comprehensive guide to building RAG-based LLM applications for production
github.com/ray-project
discuss
3 years ago
richardliaw
3 points
7.
▲
An experimental distributed execution engine from Berkeley
github.com/ray-project
discuss
9 years ago
eb0la
3 points
8.
▲
Ray: Unified framework for scaling AI and Python applications
github.com/ray-project
discuss
2 years ago
selvan
2 points
9.
▲
LLMPerf Leaderboard
github.com/ray-project
discuss
2 years ago
ZeljkoS
2 points
10.
▲
Ray – an open source project for scaling AI workloads
github.com/ray-project
discuss
3 years ago
richardliaw
2 points
11.
▲
Ray 1.4.0
github.com/ray-project
discuss
5 years ago
robertnishihara
2 points
12.
▲
Ray – Build machine learning applications at any scale
github.com/ray-project
discuss
6 years ago
snooty
2 points
13.
▲
Ray: An experimental distributed execution engine
github.com/ray-project
discuss
9 years ago
blopeur
2 points
14.
▲
Comparison: Dask vs. Ray
github.com/ray-project
discuss
2 years ago
Bluestein
1 points
15.
▲
Evaluate Multiple LLMs Easily
github.com/ray-project
discuss
3 years ago
fzliu
1 points
16.
▲
Distributed XGBoost on Ray
github.com/ray-project
discuss
5 years ago
robertnishihara
1 points
17.
▲
A fast and simple framework for building and running distributed applications
github.com/ray-project
discuss
7 years ago
minimaxir
1 points
18.
▲
Show HN: Phylogenetic Tree of All Life
discuss
7 years ago
kekeke
3 points