Holistic Evaluation of Language Models (HELM), a framework to increase the transparency of language models (https://arxiv.org/abs/2211.09110). This framework is also used to evaluate text-to-image models in Holistic Evaluation of Text-to-Image Models (HEIM) (https://arxiv.org/abs/2311.04287).
The preferred way to run models is to stand up an inference server (e.g., Triton + TensorRT or vLLM or TGI) locally and then hit it from HELM as an API. This way, HELM can benefit from all the crazy inference optimizations that are done. We need to demonstrate a proof of concept and write docs for this.
The preferred way to run models is to stand up an inference server (e.g., Triton + TensorRT or vLLM or TGI) locally and then hit it from HELM as an API. This way, HELM can benefit from all the crazy inference optimizations that are done. We need to demonstrate a proof of concept and write docs for this.