Huawei's deep learning framework with automatic differentiation and graph-mode execution, installed with Python bindings for model training and inference. Built and maintained by WIEWAVE for Azure Marketplace, on Ubuntu and Debian.
| Built & maintained by | WIEWAVE |
|---|---|
| Category | AI & Machine Learning |
| Operating systems | Ubuntu, Debian |
| Marketplaces | Azure Marketplace |
| Offer types | Public listing, with private offers on request |
| Marketplace | Status |
|---|---|
| Azure Marketplace | Published |
| AWS Marketplace | Available on request |
| Google Cloud Marketplace | Available on request |
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.
Packages Mistral 7B weights together with an inference server and Python dependencies so several fine-tuned variants can be served from one GPU instance.
Ships both Mistral 7B and the long-context MistralLite 7B checkpoints with a serving stack, letting either model be loaded for text generation.
MLflow tracking server with a PostgreSQL backend and object-store artifact root, so experiments survive the instance.
C++ machine learning library covering classification, regression, clustering and dimensionality reduction, installed with headers, command-line tools and Python bindings.
OpenMMLab toolbox for text detection and recognition, providing PyTorch models and inference scripts for OCR on documents and scene images.
Training and fine-tuning codebase for large language models from MosaicML, shipping Composer, MPT recipes and GPU-ready PyTorch dependencies.
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.
