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Description
Easily train and deploy large-scale AI models with just a single command by pointing to your S3 bucket—then let us take care of everything else, including orchestration, efficiency, node failures, and infrastructure management. The process is straightforward and scalable, allowing you to utilize MosaicML to train and serve large AI models using your own data within your secure environment. Stay ahead of the curve with our up-to-date recipes, techniques, and foundation models, all developed and thoroughly tested by our dedicated research team. With only a few simple steps, you can deploy your models within your private cloud, ensuring that your data and models remain behind your own firewalls. You can initiate your project in one cloud provider and seamlessly transition to another without any disruptions. Gain ownership of the model trained on your data while being able to introspect and clarify the decisions made by the model. Customize content and data filtering to align with your business requirements, and enjoy effortless integration with your existing data pipelines, experiment trackers, and other essential tools. Our solution is designed to be fully interoperable, cloud-agnostic, and validated for enterprise use, ensuring reliability and flexibility for your organization. Additionally, the ease of use and the power of our platform allow teams to focus more on innovation rather than infrastructure management.
Description
If you have experience with cloud storage, understanding buckets will be straightforward for you. However, in contrast to conventional cloud services, buckets utilize open and decentralized protocols like IPFS and Libp2p. They can be employed to host websites, data, and applications directly from buckets. You can easily navigate your Buckets through the Hub gateway. Additionally, you can render web content within your Bucket to create a persistent website. Updates can be automatically shared on IPFS by using IPNS. Organizations can manage Buckets collaboratively, facilitating teamwork. You also have the option to establish private Buckets, allowing your app users a secure place to store their data. For long-term security and file accessibility, you can archive Bucket data on Filecoin. To initiate a Bucket in your current working directory, you first need to initialize it. This initialization can be done with an existing UnixFS DAG from the IPFS network or by interactively importing it into an existing bucket. Furthermore, you can create buckets that can be shared among all members of your organization, enhancing collaborative efforts. It's a flexible solution that caters to diverse storage needs.
API Access
Has API
API Access
Has API
Integrations
Amazon Web Services (AWS)
Filecoin
Google Cloud Platform
IPFS
MPT-7B
Oracle Cloud Infrastructure
Polygon (Matic)
Python
Stable Diffusion
Integrations
Amazon Web Services (AWS)
Filecoin
Google Cloud Platform
IPFS
MPT-7B
Oracle Cloud Infrastructure
Polygon (Matic)
Python
Stable Diffusion
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
MosaicML
Country
United States
Website
www.mosaicml.com
Vendor Details
Company Name
Textile
Founded
2016
Website
docs.textile.io/buckets/
Product Features
Artificial Intelligence
Chatbot
For Healthcare
For Sales
For eCommerce
Image Recognition
Machine Learning
Multi-Language
Natural Language Processing
Predictive Analytics
Process/Workflow Automation
Rules-Based Automation
Virtual Personal Assistant (VPA)
Machine Learning
Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization