Versions:

0.4.7
0.4.6
0.4.5
0.4.4
0.4.1
0.3.41
0.3.40
0.3.39
0.3.38
0.3.37
0.3.35
0.3.34
0.3.33
0.3.30
0.3.29
0.3.28
0.3.26
0.3.25
0.3.24
0.3.23
0.3.22
0.3.21
0.3.20
0.3.19
0.3.18
0.3.16
0.3.12
0.3.11
0.3.10
0.3.9
0.3.8
0.3.7
0.3.6
0.3.5
0.3.4
0.3.3
0.3.2
0.3.1
0.3.0
0.2.28
0.2.27
0.2.26

Harbor 0.4.7 is a containerized LLM toolkit designed to let developers, data scientists, and DevOps teams spin up complete large-language-model environments with a single CLI command. Released as the forty-second iterative build since the project began, the software packages pre-configured LLM backends, REST and gRPC APIs, web front-ends, and supporting micro-services into lightweight containers that can be orchestrated on any Docker-compatible host. Typical use cases include rapid prototyping of generative-AI features, hosting private chat interfaces inside corporate firewalls, benchmarking multiple models side-by-side, or providing GPU-accelerated inference endpoints for mobile and web clients. The companion desktop application exposes a visual dashboard for starting, stopping, and monitoring services, while the command-line client supports declarative YAML profiles that reproduce entire stacks across laptops, on-prem servers, and cloud instances. Because all components are version-locked inside isolated containers, Harbor eliminates dependency conflicts and allows concurrent execution of competing frameworks such as PyTorch, TensorFlow, or llama.cpp without altering the host OS. The toolkit is catalogued under Developer Tools / AI & Machine Learning and is available for free on get.nero.com, where downloads are delivered through trusted Windows package sources like winget, always serving the latest build and enabling batch installation alongside other applications.

Tags:

ai 171

large-language-model 80

llm 100

ollama 21