The author also provides a background on the two categories of tools for model inference: Inference servers and Model Optimization. Detailed notes on how to use each tool, including code snippets, are provided. The author concludes that while all tools have their merits, if optimizing for latency is the primary goal, vLLM would be the best choice. However, the author also notes that the choice of tool may depend on specific needs, such as whether a web user-interface is required.
Key takeaways:
- The author conducted a study to compare various tools for optimizing latency in open source LLMs. The tools compared included CTranslate2, vLLM, Text Generation Inference (TGI), and others.
- CTranslate2 was found to be the fastest and easiest to use. vLLM was also fast, but CTranslate2 was faster. TGI was an okay option but not as fast as vLLM or CTranslate2.
- The author also provided rough benchmarks for these tools, with variables such as batch size, GPU used, and max output tokens held constant. The goal was to get a general sense of how these tools compare to each other out of the box.
- It was noted that the license for TGI was changed to be more restrictive, which may interfere with certain commercial uses. The author also provided detailed notes on how to use each tool, including code snippets and commands.