Python framework for packaging machine learning models into production services with REST and gRPC endpoints, adaptive batching, containerisation and a model store. Built and maintained by WIEWAVE for Azure Marketplace, AWS Marketplace and Google Cloud Marketplace, on Ubuntu and Debian.
| Built & maintained by | WIEWAVE |
|---|---|
| Category | AI & Machine Learning |
| Operating systems | Ubuntu, Debian |
| Marketplaces | Azure Marketplace, AWS Marketplace and Google Cloud Marketplace |
| Offer types | Public listing, with private offers on request |
| Marketplace | Status |
|---|---|
| Azure Marketplace | Published |
| AWS Marketplace | Published |
| Google Cloud Marketplace | Published |
Need it on another marketplace, or as a private offer for your organisation? cloud@wiewave.com
Each image follows its distribution's own provisioning model, package manager and security tooling — not one build relabelled several times.
LTS and interim releases, Minimal and Pro variants, built to Canonical's cloud-image conventions.
Stable and oldstable, with backports where a workload needs a newer runtime than the release ships.
The same four steps behind every offer we've published, including the hardening and CIS Benchmark checks every build goes through.
The distribution, licensing model and target marketplaces are agreed before anything is built.
Packer templates, Ansible provisioning and a pinned package set — then hardened, scanned and checked against the CIS Benchmark for its distribution.
Taken through each cloud's own certification pipeline before it goes live on the marketplace.
Rebuilt on the upstream security cadence and re-published, with old versions retired without breaking deployments.
If yours isn't here, ask our marketplace team directly.
GPU-ready training and inference images with drivers, CUDA and frameworks already matched to each other.
Transformer language model for text classification, question answering and embeddings, shipped with pretrained weights, tokenizers and a framework for fine-tuning.
Class-conditional generative adversarial network for high-resolution image synthesis, provided with pretrained weights and inference scripts for sampling from ImageNet categories.
Text-to-image generation tool that steers BigGAN with CLIP guidance to synthesise pictures from prompts, installed with PyTorch and GPU dependencies.
Multilingual large language model fine-tuned from BLOOM for instruction following across dozens of languages, served with transformers and inference dependencies.
Deep learning framework from Berkeley Vision and Learning Center, shipped with Python bindings, the reference model zoo and CPU inference dependencies.
French-language RoBERTa model packaged with Hugging Face Transformers and PyTorch for text classification, named entity recognition and other NLP tasks.
Tell us the distribution, the marketplace and the commercial model — we'll build, certify and publish it as a public listing or a private offer.
