vLLM-0.0.1

vLLM is a high-performance, low-latency, and memory-efficient library designed for serving large language models (LLMs) at scale.

lomas-server-0.3.7

Lomas is a remote access platform developed by the Swiss Federal Statistical Office allowing National Statistical Offices to offer eyes-off data science on private datasets while controlling disclosure risk. The platform relies on a service that is meant to be deployed on-premises and allows accredited users to apply differentially private algorithms on private datasets using a dedicated client Python library.

lomas-server-0.3.6

Lomas is a remote access platform developed by the Swiss Federal Statistical Office allowing National Statistical Offices to offer eyes-off data science on private datasets while controlling disclosure risk. The platform relies on a service that is meant to be deployed on-premises and allows accredited users to apply differentially private algorithms on private datasets using a dedicated client Python library.

lomas-server-0.3.5

Lomas is a remote access platform developed by the Swiss Federal Statistical Office allowing National Statistical Offices to offer eyes-off data science on private datasets while controlling disclosure risk. The platform relies on a service that is meant to be deployed on-premises and allows accredited users to apply differentially private algorithms on private datasets using a dedicated client Python library.

lomas-server-0.3.4

Lomas is a remote access platform developed by the Swiss Federal Statistical Office allowing National Statistical Offices to offer eyes-off data science on private datasets while controlling disclosure risk. The platform relies on a service that is meant to be deployed on-premises and allows accredited users to apply differentially private algorithms on private datasets using a dedicated client Python library.

lomas-server-0.3.1

Lomas is a remote access platform developed by the Swiss Federal Statistical Office allowing National Statistical Offices to offer eyes-off data science on private datasets while controlling disclosure risk. The platform relies on a service that is meant to be deployed on-premises and allows accredited users to apply differentially private algorithms on private datasets using a dedicated client Python library.

lomas-server-0.3.0

Lomas is a remote access platform developed by the Swiss Federal Statistical Office allowing National Statistical Offices to offer eyes-off data science on private datasets while controlling disclosure risk. The platform relies on a service that is meant to be deployed on-premises and allows accredited users to apply differentially private algorithms on private datasets using a dedicated client Python library.

lomas-server-0.1.2

Lomas is a remote access platform developed by the Swiss Federal Statistical Office allowing National Statistical Offices to offer eyes-off data science on private datasets while controlling disclosure risk. The platform relies on a service that is meant to be deployed on-premises and allows accredited users to apply differentially private algorithms on private datasets using a dedicated client Python library.

lomas-server-0.1.0

Lomas is a remote access platform developed by the Swiss Federal Statistical Office allowing National Statistical Offices to offer eyes-off data science on private datasets while controlling disclosure risk. The platform relies on a service that is meant to be deployed on-premises and allows accredited users to apply differentially private algorithms on private datasets using a dedicated client Python library.

lomas-server-0.0.30

Lomas is a remote access platform developed by the Swiss Federal Statistical Office allowing National Statistical Offices to offer eyes-off data science on private datasets while controlling disclosure risk. The platform relies on a service that is meant to be deployed on-premises and allows accredited users to apply differentially private algorithms on private datasets using a dedicated client Python library.