  Language models (LMs) have become ubiquitous in both NLP research and in
commercial product offerings. As their commercial importance has surged, the
most powerful models have become closed off, gated behind proprietary
interfaces, with important details of their training data, architectures, and
development undisclosed. Given the importance of these details in
scientifically studying these models, including their biases and potential
risks, we believe it is essential for the research community to have access to
powerful, truly open LMs. To this end, we have built OLMo, a competitive, truly
Open Language Model, to enable the scientific study of language models. Unlike
most prior efforts that have only released model weights and inference code, we
release OLMo alongside open training data and training and evaluation code. We
hope this release will empower the open research community and inspire a new
wave of innovation.
