Sean Sheng

[Sean Sheng @sean_sheng]

Beside wide discussed performance improvement in @vllm 0.6, we are particularly excited about the introduction of auto tool_choice and JSON response_format. vLLM further bridges the gap between open and close source LLMs when it comes to function calling.

https://t.co/zRZepkRAye

[BentoML @bentomlai]

🚀 OpenLLM 0.6 is out providing fast inference speed! Check out our video comparing #OpenLLM and #Ollama handling concurrent requests on the Llama 3 8B model. Ollama is ideal for local LLM deployment, but it is not designed for high concurrency scenarios essential for deployments in the cloud, powering applications with a large number of users.

OpenLLM enables you to run any open-source model as OpenAI-compatible endpoints with just a single command. It supports a broad array of models like Llama 3, Mistral, and Qwen 2, including those fine-tuned with proprietary datasets and quantized versions.

Ready to speed up your AI deployments? See the OpenLLM repo https://t.co/PVhLM89LSc
#BentoML #OpenSource

[BentoML @bentomlai]

🚀 Just released a comprehensive benchmark on #LLM #inference backends (https://t.co/JLZzfLmxN8)! Essential for every AI/ML engineer to know how these tools can enhance the performance & reliability of LLMs.

In our benchmark study, we evaluated the serving performance of #Llama3 with vLLM, LMDeploy, MLC-LLM, TensorRT-LLM, and Hugging Face TGI on #BentoCloud, and shared our findings on quantization, model support, hardware limitations, and developer experience.

Read the full report for detailed performance metrics & recommendations. Improve your LLM serving today!
#AI #MachineLearning #OpenSource #BentoML #vLLM #LMDeploy #MLCLLM #TensorRTLLM #TGI

[Sean Sheng @sean_sheng]

@suchenzang Thank you for the insightful post. Do you believe it's only the "most powerful models" that can effectively address the challenges enterprises are facing? Could finely-tuned, smaller models deliver comparable or even superior performance, all while being more cost-efficient?

[Sean Sheng @sean_sheng]

@DanBrownUSA @langchain @bentomlai Thanks, Dan. You can follow the steps listed in the README and start the BentoML server in minutes.