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CITATION.cff
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cff-version: 1.2.0
title: 'OpenLLM: Operating LLMs in production'
message: >-
If you use this software, please cite it using these
metadata.
type: software
authors:
- given-names: Aaron
family-names: Pham
email: [email protected]
orcid: 'https://orcid.org/0009-0008-3180-5115'
- given-names: Chaoyu
family-names: Yang
email: [email protected]
- given-names: Sean
family-names: Sheng
email: [email protected]
- given-names: Shenyang
family-names: ' Zhao'
email: [email protected]
- given-names: Sauyon
family-names: Lee
email: [email protected]
- given-names: Bo
family-names: Jiang
email: [email protected]
- given-names: Fog
family-names: Dong
email: [email protected]
- given-names: Xipeng
family-names: Guan
email: [email protected]
- given-names: Frost
family-names: Ming
email: [email protected]
repository-code: 'https://github.com/bentoml/OpenLLM'
url: 'https://bentoml.com/'
abstract: >-
OpenLLM is an open platform for operating large language
models (LLMs) in production. With OpenLLM, you can run
inference with any open-source large-language models,
deploy to the cloud or on-premises, and build powerful AI
apps. It has built-in support for a wide range of
open-source LLMs and model runtime, including StableLM,
Falcon, Dolly, Flan-T5, ChatGLM, StarCoder and more.
OpenLLM helps serve LLMs over RESTful API or gRPC with one
command or query via WebUI, CLI, our Python/Javascript
client, or any HTTP client. It provides first-class
support for LangChain, BentoML and Hugging Face that
allows you to easily create your own AI apps by composing
LLMs with other models and services. Last but not least,
it automatically generates LLM server OCI-compatible
Container Images or easily deploys as a serverless
endpoint via BentoCloud.
keywords:
- MLOps
- LLMOps
- LLM
- Infrastructure
- Transformers
- LLM Serving
- Model Serving
- Serverless Deployment
license: Apache-2.0
date-released: '2023-06-13'