log4net by: The Apache Software Foundation

log4net is a tool to help the programmer output log statements to a variety of output targets. In case of problems with an application, it is helpful to enable logging so that the problem can be located. With log4net it is possible to enable logging at runtime without modifying the application binary. The log4net package is designed so that log statements can remain in shipped code without incurring a high performance cost. It follows that the speed of logging (or rather not logging) is crucial. At the same time, log output can be so voluminous that it quickly becomes overwhelming. One of the distinctive features of log4net is the notion of hierarchical loggers. Using these loggers it is possible to selectively control which log statements are output at arbitrary granularity. log4net is designed with two distinct goals in mind: speed and flexibility

LLamaSharp.Backend.Cuda12.Windows by: llama.cpp Authors

LLamaSharp.Backend.Cuda12.Windows contains the Windows binaries for LLamaSharp with Cuda12 support.

KRE-CoreCLR-x86 by: Microsoft

The K Runtime Environment for CoreCLR x86

LiteDB by: Maurício David

LiteDB - A lightweight embedded .NET NoSQL document store in a single datafile

K4os.Compression.LZ4.Streams by: Milosz Krajewski

Port of LZ4 compression algorithm for .NET

KubernetesClient.Models by: The Kubernetes Project Authors

Client library for the Kubernetes open source container orchestrator.

LamarCodeGeneration by: Jeremy D. Miller

Code Generation Chicanery for .Net

Libuv by: Libuv

Multi-platform support library with a focus on asynchronous I/O.

LamarCompiler by: Jeremy D. Miller

Runtime Roslyn Compilation and Code Generation Chicanery

LLamaSharp by: Rinne Martin Evans jlsantiago and all the other contributors in https://github.com/SciSharp/LLamaSharp/graphs/contributors.

LLamaSharp is a cross-platform library to run 🦙LLaMA/Mtmd model (and others) in your local device. Based on [llama.cpp](https://github.com/ggerganov/llama.cpp), inference with LLamaSharp is efficient on both CPU and GPU. With the higher-level APIs and RAG support, it's convenient to deploy LLM (Large Language Model) in your application with LLamaSharp.

LLamaSharp.Backend.Cuda12 by: llama.cpp Authors

LLamaSharp.Backend.Cuda12 is a backend for LLamaSharp to use with Cuda12.

Lamar by: Jeremy D. Miller

Fast ASP.Net Core compatible IoC Tool, Successor to StructureMap

KubernetesClient by: The Kubernetes Project Authors

Client library for the Kubernetes open source container orchestrator.

librdkafka.redist by: Magnus Edenhill edenhill

The Apache Kafka C/C++ client library - redistributable

K4os.Hash.xxHash by: Milosz Krajewski

xxHash hash implementation for .NET

Lamar.Microsoft.DependencyInjection by: Jeremy D. Miller

Lamar Adapter for ASP.Net Core

LLamaSharp.Backend.Cpu by: llama.cpp Authors

LLamaSharp.Backend.Cpu is a backend for LLamaSharp to use with Cpu only.

LLamaSharp.Backend.Cuda12.Linux by: llama.cpp Authors

LLamaSharp.Backend.Cuda12.Linux contains the Linux binaries for LLamaSharp with Cuda12 support.

KRE-CLR-x86 by: Microsoft

The K Runtime Environment for Desktop CLR x86

KubernetesClient.Basic by: The Kubernetes Project Authors

Client library for the Kubernetes open source container orchestrator.