The Modelbit Changelog

New features, product improvements, and bug fixes from the Modelbit team
We publish product updates every Friday. Subscribe to receive a monthly changelog roundup.
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Week of December 4, 2023

Check out the new Model Overview page! See a useful summary of inference endpoints and training jobs in one concise view.

🛠️ More Improvements:

🐛 Bug Fixes:

Week of November 27, 2023

Redesigned git settings: We made the git settings page easier to use and more visually pleasing.

🛠️ More Improvements:

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Week of November 20, 2023

A10G GPUs with 24GB VRAM have arrived at Modelbit! You can change the compute environment of any version of any deployment after it is deployed. You can also set the compute environment using git or with the require_gpu parameter of mb.deploy. Learn more.

🛠️ More Improvements:

Week of November 13, 2023

Improved the layout of the Deployments page, paying special attention to displaying long deployment names!

🛠️ More Improvements:

Week of November 06, 2023

GPUs are now enabled for all customers! Toggle on GPUs in the UI for inference endpoints, or select a box with a GPU for training jobs, and feel the power course through you.

🛠️ Improvements:

🐛 Bug Fixes:

🎃 Week of October 30, 2023

🛠️ Improvements:

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Week of October 23, 2023

Merge deployments from within Modelbit! Now you can merge your deployments to main (or any other branch) without tabbing over to GitHub. This means we've also turned on branch protection even when you don't have a git integration set up.

Training jobs now show CPU and Memory Usage Statistics!

🛠️ More Improvements:

🐛Bug Fixes:

Week of October 16, 2023

Deployments Sidebar Redesign: We reorganized the Deployments sidebar into sections! If you're looking for the Notebooks section, it's been folded into the Source Code section.

More Improvements:

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Week of October 9, 2023

Slack Alerts: You can now get Slack alerts when datasets fail to update and when training jobs fail. Learn more.

More Improvements:

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Week of October 2, 2023

Llama 2: You can now deploy Llama 2 Models in Modelbit with vastly improved support for llama.cpp. Learn more.

More Improvements:

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Week of September 25, 2023

Training ML Models on GPUs: We've added support for training models on GPUs and on much larger boxes! Boxes even larger than the ones chooseable in the product are available upon request. Learn more.

Large Python Environments: We made it faster to build large Python environments as part of deploying large models! For example, the time to build a 6GB environment for OWL-ViT on JAX has been reduced from ~280s to ~180s. We are continuing to work on making it faster to build environments and deploy models.

More Improvements:

🐛 Bug Fixes: 

Week of September 18, 2023


Week of September 11, 2023

Async API: For long-running inferences, you can now supply a webhook for Modelbit to call you back when your results are ready. Learn more.

More Improvements:

🐛 Bug Fixes:

Week of September 4, 2023

Endpoints Improvement: Modelbit endpoints can now point to deployments on any git branch. This should make it seamless to ship endpoint changes from a branch using a merge request. Learn more.

Model Registry Improvements:

More Improvements and 🐛 Bug Fixes:

Week of August 28, 2023

🎉 Announcing the Modelbit Model Registry!

More Improvements:

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Week of August 21, 2023

GPU Cold Start Times: Your models running on GPUs will now have much faster cold start times.

CORS Headers: We added support for CORS Headers so you can call Modelbit directly from a JS Client.

More Improvements:

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Week of August 14, 2023

Common Files: Files that you commonly use in model deployments can be checked into Modelbit as common files. Common files are automatically added to all deployment environments.

More Improvements:

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Week of August 7, 2023

PyTorch environment detection: We’ve made a number of improvements to environment auto-detection for PyTorch models.

Runtime Context Commands: Your code can now learn about its runtime context when running in Modelbit! In particular:

More Improvements:

Week of July 31, 2023

Role based access controls: You can now control which users can deploy models, change settings, and update billing information with role based access controls (RBAC) to make it easier for you to manage permissions for existing users and new users.

More Improvements:

Week of July 24, 2023

Improved Deployment Card Layout: When you are working on a branch, the deployments you’re working on are promoted to the top of the list of deployment cards for quicker access.

Deployment Logs Webhook: We’ve added a deployment logs webhook so that you can send Modelbit logs in real time to a variety of logs ingestion services. This allows you to do things like ingest Modelbit logs into a database for custom reporting.

Arize Integration: We’re excited to announce that we’ve built an integration with Arize! This new integration will support detailed inference monitoring and analysis for models running in Modelbit.

More Improvements:

Week of July 17, 2023

Logging images to Modelbit: You can now log images in addition to text in Modelbit! Use log_image to log matplotlib Figures or image files to Modelbit. Those images will be rendered directly in the logs viewer.

More Improvements:

Week of July 10, 2023

Protected branches for git workflows: Teams using Modelbit can now protect certain branches to ensure all changes come from approved merge requests. Learn More.

Weights & Biases Integration: We've added this new integration to enable training in Modelbit and experiment analysis with Weights & Biases. Learn More.

More Improvements:

Week of July 3, 2023

Support for AWS Athena: In addition to Snowflake and Redshift, Modelbit customers can now make datasets and feature stores by querying Athena warehouses.

REST API Performance: We’ve improved the performance of inferences using the REST API with Keep Warm by reducing network latency up to 50%.

More Improvements:

Week of June 26, 2023

More sophisticated drift charts: In models that return JSON (i.e. most of them) Modelbit will plot the results from every JSON key on the drift chart.

More Improvements:

Week of June 19, 2023

Training Jobs 2.0! The API and web UI for training jobs got a major overhaul! It's much easier to kick off an arbitrary job from a notebook even without an associated deployment. The API for jobs got a whole lot simpler. You can fetch the results of any job run from a notebook, and you can manually look at results and then decide whether to redeploy your deployment with the results of that job run! Learn more.

More improvements:

Week of June 12, 2023

Improved logs viewer: Standard out and standard error are now separated for easy scanning. Plus, the logs viewer now supports way more than 5,000 characters per log line.

More improvements:

Week of June 5, 2023

Automatic system package detection: When Python packages depend on Linux system packages, those system packages are now automatically included in runtime environments as necessary. For example, all Python environments that include torch now also include build-essential.

Week of May 26, 2023

Deploy with extra files: Bring extra local files to production alongside your deployment with the extra_files parameter on modelbit.deploy. Learn more.

Week of May 15, 2023

Secrets Management: Secure storage and management for your AWS Secret Access Keys, OpenAI API Keys, and any other secrets to make them securely available at inference time. Learn more.

Week of May 8, 2023

Automatic notebook environment detection: When deploying from a notebook, Modelbit now automatically detects which Python packages your code depends on, and the versions of those packages, and makes sure they're installed correctly in production. You should no longer need to specify Python packages at deploy time in most cases.

Dependences from remote git repos: Include Python packages in your deployment that are installed from remote git servers, like detectron2, segment-anything, and pretty much everything from Facebook Research! Specify them just like you would in a requirements.txt file.

Week of May 1, 2023

Brand new infrastructure for big neural nets! Your Tensorflow models, PyTorch models, big fancy transformers, and other deep neural nets now run on infrastructure dedicated to their performance! Modelbit will detect models with specific memory and compute needs, including deep neural nets, and deploy them to specific infrastructure optimized for their stability and performance.

Week of April 24, 2023

Deploy with Private Packages and Modules: Add your internal helper and utility packages to Modelbit so they'll be available for all of your deployments in production! Run modelbit.add_module to add an imported module or modelbit.add_package to add a Python package. Learn more.

Week of April 17, 2023

Archive your deployments when you're no longer actively working on them so you can keep a clean workspace, especially on your development branch!

Week of March 20, 2023

Slack Alerts: Get alerted whenever your model misbehaves! Modelbit now integrates with Slack so you can get alerted any time a model throws an exception for any reason. Learn more.

Singleton Mode is an easier API for getting a single inference rather than inferences in batches.

Logs are much easier to read for complex inputs, outputs, and log lines.

Week of March 13, 2023

Endpoints: A/B test your models, send traffic to multiple models at once, canary test your models and more! Learn more.

Eppo Integration: Integrate with Eppo to take advantage of even more sophisticated A/B testing functionality. Learn more.

Week of March 6, 2023

Variable Size Job Runners: Training jobs can now be run on a variety of different CPU and memory configurations, for when you need to burst up to 120GB RAM to train your models. Learn more.

Support for Python 3.11! 🐍