WizModel

WizModel: Run ML Models in the Cloud at Scale

WizModel is a platform that lets you run machine learning models with minimal setup. You can access thousands of models (language, vision, audio, video, upscaling, image restoration, etc.), package your own models with Cog2, deploy to a scalable API, and pay only for actual usage.

---

How WizModel Works

1. 01 Run: Use the Python library or REST API to run models without deep ML knowledge. Install the Cog2 tool, login, and call predictions directly.
2. 02 Push: Package your model in a standard, production-ready container using Cog2. Define the environment in cog.yaml, build a Docker image, and push to WizModel.
3. 03 Scale: Deploy models at scale with automatic API generation and scalable GPU clusters. Auto-scale up for traffic, scale down to zero when idle, pay by the second.
4. 04 Earn Cash: If others use your published model via the API, you’ll earn a portion of their usage (coming soon).

---

Getting Started

• Install Cog2 locally and log in (or use API directly).
• Package your model with cog.yaml and a predict.py predictor.
• Build, push, and deploy to WizModel’s scalable infrastructure.

Model Catalog and Capabilities

• Language models (text understanding and generation)
• Video creation and editing
• Image generation and diffusion-based models
• Super-resolution and image restoration
• Image-to-text and text-to-image pipelines

How to Use WizModel: Step-by-Step

• 01 Run: Define input payload and version, then call the REST API or use the Python client to get predictions.
• 02 Push: Prepare environment (Python version and required packages), create cog.yaml, and push the container to WizModel.
• 03 Scale: Run predictions via a scalable API with automatic scaling and pay-per-second pricing.

---

Safety and Legal Considerations

• Use models responsibly and respect licensing and data privacy. Follow platform terms for API usage and model publication.

Core Features

• Access thousands of ready-to-use ML models (text, image, video, audio, and more)
• Run models locally via Python or REST API without ML expertise
• Package and deploy your own models with Cog2 in a production-ready container
• Automatic API generation and scalable deployment on GPUs
• Pay only for actual runtime (per-second billing)
• Easy model publishing with potential revenue-sharing (coming soon)
• Large model catalog and community-contributed models