French-language RoBERTa model packaged with Hugging Face Transformers and PyTorch for text classification, named entity recognition and other NLP tasks. 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.
Gradient boosting library from Yandex with native categorical feature handling, installed alongside Python bindings, GPU training support and Jupyter notebooks.
Define-by-run deep learning framework for Python, preinstalled with CuPy GPU arrays, NumPy and Jupyter for building and training neural networks.
Python library for building conversational bots that learn from example dialogue corpora, installed with its storage adapters and training utilities.
Preconfigured MLOps stack combining pipeline orchestration, a model registry and automated training, evaluation and deployment steps for continuous delivery of models.
Development environment with Anthropic's Claude command-line tooling and API SDKs installed for building applications and agents against Claude models.
MLOps platform bundling experiment tracking, dataset versioning, pipeline orchestration and remote agents, backed by MongoDB, Elasticsearch and Redis on the server.
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.
