In this post we walk through the steps to deploy DINOv2 as a REST API endpoint using Modelbit.
Discover how to effectively manage and track model versions for rapid experimentation, deployment, and rollback in this comprehensive guide. Implement model versioning and ensure seamless management and deployment of ML models.
Learn how to deploy the OpenAI Whisper-Large-v2 model for speech recognition and transcription using Modelbit. Use speech recognition models and learn how to integrate them into your applications.
This tutorial will teach you how to use LLaMA-2 and LangChain to build a text summarization endpoint that you can deploy as an inference service with Modelbit.
This tutorial guides you through deploying a pre-trained BERT model as a real-time REST API endpoint for efficient and scalable text classification in production using Modelbit.
In this tutorial, we'll walk through the steps to deploy a ResNet-50 image classification model to a REST API Endpoint.
TAPAS is a BERT-based model from Google that can answer questions about a table with natural language. In this post we show how you can deploy a TAPAS model to a REST API in minutes.
In this article, you will learn how to deploy the Grounding DINO Model as a REST API endpoint for object detection using Modelbit.
OWL-ViT is a new object detection model from the team at Google Research. In this post we walk through how to deploy an OWL-ViT model to a REST API.
In this article we walk through how we built a Docker environment build time predictor as a key feature in our product and deployed it into production using Modelbit.
Can you go from idea to inference in minutes? That’s what we set out to answer when we tested using Deepnote AI and Modelbit together. In this article we walk through the process of deciding on a model, building and training it using AI, and deploying it to production with one line of code via Modelbit.
In their paper, Facebook's new Segment-Anything model shows off impressive image recognition performance, beating even some models that know what type of image they’re looking for. In this tutorial we'll talk through the steps to deploy a Segment-Anything model to a REST Endpoint.
With modern data science and machine learning, it’s easier than ever to predict whether a customer is going to churn. With the right training data and modeling libraries, we can quickly train a model that scores a customer’s likelihood of churning.
Five tricks we've learned the hard way to make working with Pandas DataFrames easier for data scientists everywhere.
How to call lambda functions efficiently in batch from Amazon Redshift. A helpful guide for those struggling with slow calls to Lambda from Redshift when doing batch inference for machine learning.
A simple and elegant way to develop machine learning models in Hex, and then deploy them to the cloud with Modelbit
How to build a lead scoring model for a b2b business and deploy it to production so it can be used in both online inference via REST API, and offline batch scoring via SQL function.
A step-by-step guide to building ML models in Deepnote and deploying them to Snowflake using Modelbit.
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