Integrate Model Zoo in Slack
with Axolo

Model Zoo logo

+

Slack logo

Developed by

model-zoo

Deployment Continuous
Free

What is Model Zoo about?

Model Zoo is a platform-as-a-service that simplifies the deployment of machine learning models by providing an easy-to-use solution. It is similar to Heroku, but instead of deploying generic apps, it focuses on deploying machine learning models. With Model Zoo, you can deploy your model to an HTTP endpoint with just one line of code, making it easy for users to integrate their models into their applications. The service supports popular machine learning frameworks such as TensorFlow and Hugging Face Transformers, and provides quickstarts to help users get started quickly. The product is free to try for deploying up to three models, which makes it an ideal solution for startups and small businesses that need to deploy a few models without investing in expensive infrastructure. With Model Zoo, users can deploy their machine learning models with ease and focus on building their applications instead of worrying about the deployment process.

What are Model Zoo features and benefits?

- Model Zoo is a model deployment platform-as-a-service
- Focuses on ease-of-use
- Deploy machine learning models to an HTTP endpoint with a single line of code
- Supports TensorFlow and Hugging Face Transformers
- Free to try for deploying up to 3 models
- Quickstarts available on Google Colab

What is Model Zoo pricing?

The pricing for Model Zoo's Free Tier is $0.

Integrate Model Zoo in Slack with Axolo

Integrating Model Zoo in Slack with Axolo is beneficial because it allows engineers to quickly and easily review code changes that involve machine learning models. With Axolo, engineers can open an ephemeral channel for each pull request and invite the right person to act on the code review, while also having access to the deployed machine learning models through Model Zoo.

Learn more about Model Zoo on the GitHub marketplace.

Model Zoo GitHub integration screenshots

Monitor: Get observability into model performance, feature distributions, and prediction metrics: all automatically configured out-of-the-box

Monitor: Get observability into model performance, feature distributions, and prediction metrics: all automatically configured out-of-the-box

Debug: Quickly validate model performance with tooling optimized for your modeling use case
Document: Autogenerated and editable markdown page for documenting metadata with every model

They are merging pull requests with us everyday

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