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Description
Maintain your usual routine while working within Jupyter Notebooks or any Python setting. Just invoke modelbi.deploy to launch your model, allowing Modelbit to manage it — along with all associated dependencies — in a production environment. Machine learning models deployed via Modelbit can be accessed directly from your data warehouse with the same simplicity as invoking a SQL function. Additionally, they can be accessed as a REST endpoint directly from your application. Modelbit is integrated with your git repository, whether it's GitHub, GitLab, or a custom solution. It supports code review processes, CI/CD pipelines, pull requests, and merge requests, enabling you to incorporate your entire git workflow into your Python machine learning models. This platform offers seamless integration with tools like Hex, DeepNote, Noteable, and others, allowing you to transition your model directly from your preferred cloud notebook into a production setting. If you find managing VPC configurations and IAM roles cumbersome, you can effortlessly redeploy your SageMaker models to Modelbit. Experience immediate advantages from Modelbit's platform utilizing the models you have already developed, and streamline your machine learning deployment process like never before.
Description
NetsPresso serves as an advanced platform for optimizing AI models with a strong focus on hardware awareness. It facilitates on-device AI applications across various sectors, making it an essential tool for developing hardware-aware AI models. The incorporation of lightweight models like LLaMA and Vicuna allows for highly efficient text generation capabilities. Additionally, BK-SDM represents a streamlined version of Stable Diffusion models. Vision-Language Models (VLMs) effectively merge visual information with natural language processing. By addressing challenges associated with cloud and server-based AI solutions—such as limited connectivity, high expenses, and privacy concerns—NetsPresso stands out in the field. Furthermore, it operates as an automated model compression platform, effectively reducing the size of computer vision models to ensure they can function independently on smaller and less powerful edge devices. By optimizing target models through various compression techniques, the platform successfully minimizes AI models while maintaining their performance integrity. This dual focus on efficiency and effectiveness positions NetsPresso as a leader in the field of AI optimization.
API Access
Has API
API Access
Has API
Integrations
Amazon Redshift
Arduino IDE
Arm MAP
Databricks
Deepnote
GitHub
GitLab
Google Colab
Intel SceneScape
Jupyter Notebook
Integrations
Amazon Redshift
Arduino IDE
Arm MAP
Databricks
Deepnote
GitHub
GitLab
Google Colab
Intel SceneScape
Jupyter Notebook
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Modelbit
Founded
2022
Country
United States
Website
www.modelbit.com
Vendor Details
Company Name
Nota AI
Founded
2015
Country
South Korea
Website
www.nota.ai/netspresso
Product Features
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization