Neural text-to-speech architecture that generates mel spectrograms from text for a vocoder such as WaveGlow, packaged with PyTorch and CUDA dependencies. Built and maintained by WIEWAVE for Azure Marketplace and AWS Marketplace, on Ubuntu and Debian.
| Built & maintained by | WIEWAVE |
|---|---|
| Category | AI & Machine Learning |
| Operating systems | Ubuntu, Debian |
| Marketplaces | Azure Marketplace and AWS Marketplace |
| Offer types | Public listing, with private offers on request |
| Marketplace | Status |
|---|---|
| Azure Marketplace | Published |
| AWS Marketplace | Published |
| 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.
TensorFlow with GPU support, the matching cuDNN and TensorBoard ready to serve on first launch.
Optical character recognition engine that extracts text from images and scanned documents, shipping with language training data and the Leptonica imaging library.
Gradio web interface for running and chatting with local large language models, supporting Transformers, llama.cpp and ExLlama backends plus LoRA loading.
Toolkit for converting text into dense vector embeddings and scoring semantic similarity, with pretrained sentence models in a ready Python environment.
Python framework for adversarial attacks, data augmentation and robustness testing of NLP models, integrating with Hugging Face Transformers and datasets.
Simple Python API for common natural language processing tasks including sentiment analysis, noun phrase extraction and part-of-speech tagging, built over NLTK.
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.
