  Foundation model development attracts a rapidly expanding body of
contributors, scientists, and applications. To help shape responsible
development practices, we introduce the Foundation Model Development
Cheatsheet: a growing collection of 250+ tools and resources spanning text,
vision, and speech modalities. We draw on a large body of prior work to survey
resources (e.g. software, documentation, frameworks, guides, and practical
tools) that support informed data selection, processing, and understanding,
precise and limitation-aware artifact documentation, efficient model training,
advance awareness of the environmental impact from training, careful model
evaluation of capabilities, risks, and claims, as well as responsible model
release, licensing and deployment practices. We hope this curated collection of
resources helps guide more responsible development. The process of curating
this list, enabled us to review the AI development ecosystem, revealing what
tools are critically missing, misused, or over-used in existing practices. We
find that (i) tools for data sourcing, model evaluation, and monitoring are
critically under-serving ethical and real-world needs, (ii) evaluations for
model safety, capabilities, and environmental impact all lack reproducibility
and transparency, (iii) text and particularly English-centric analyses continue
to dominate over multilingual and multi-modal analyses, and (iv) evaluation of
systems, rather than just models, is needed so that capabilities and impact are
assessed in context.
