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What is Featherless?

Featherless is an innovative provider of AI models, giving subscribers access to an ever-expanding library of Hugging Face models. With hundreds of new models emerging daily, effective tools are crucial for navigating this rapidly evolving space. No matter your application, Featherless facilitates the discovery and utilization of high-quality AI models that fit your needs. We currently support a range of LLaMA-3-based models, including LLaMA-3 and QWEN-2, with the latter being limited to a maximum context length of 16,000 tokens. In addition, we are actively working to expand the variety of architectures we support in the near future. Our ongoing commitment to innovation means that we continuously incorporate new models as they appear on Hugging Face, with plans to automate the onboarding process to encompass all publicly available models that meet our criteria. To ensure fair usage, we impose limits on concurrent requests based on the chosen subscription plan. Subscribers can anticipate output speeds ranging from 10 to 40 tokens per second, which depend on the model in use and the prompt length, thus providing a customized experience for each user. As we grow, our focus remains on further enhancing the capabilities and offerings of our platform, striving to meet the diverse demands of our subscribers. The future holds exciting possibilities for tailored AI solutions through Featherless, as we aim to lead in accessibility and innovation.

What is Azure Machine Learning?

Optimize the complete machine learning process from inception to execution. Empower developers and data scientists with a variety of efficient tools to quickly build, train, and deploy machine learning models. Accelerate time-to-market and improve team collaboration through superior MLOps that function similarly to DevOps but focus specifically on machine learning. Encourage innovation on a secure platform that emphasizes responsible machine learning principles. Address the needs of all experience levels by providing both code-centric methods and intuitive drag-and-drop interfaces, in addition to automated machine learning solutions. Utilize robust MLOps features that integrate smoothly with existing DevOps practices, ensuring a comprehensive management of the entire ML lifecycle. Promote responsible practices by guaranteeing model interpretability and fairness, protecting data with differential privacy and confidential computing, while also maintaining a structured oversight of the ML lifecycle through audit trails and datasheets. Moreover, extend exceptional support for a wide range of open-source frameworks and programming languages, such as MLflow, Kubeflow, ONNX, PyTorch, TensorFlow, Python, and R, facilitating the adoption of best practices in machine learning initiatives. By harnessing these capabilities, organizations can significantly boost their operational efficiency and foster innovation more effectively. This not only enhances productivity but also ensures that teams can navigate the complexities of machine learning with confidence.

Media

Media

Integrations Supported

Azure AI Search
Azure Container Registry
Azure Data Science Virtual Machines
Azure Database for MariaDB
Cranium
Evvox
Hugging Face
Llama 2
Llama 3.1
Llama 3.2
Llama 3.3
Microsoft Azure
Microsoft Intelligent Data Platform
ModelOp
New Relic
Omnisient
OpenAI
Slingshot
Superwise
Wizata

Integrations Supported

Azure AI Search
Azure Container Registry
Azure Data Science Virtual Machines
Azure Database for MariaDB
Cranium
Evvox
Hugging Face
Llama 2
Llama 3.1
Llama 3.2
Llama 3.3
Microsoft Azure
Microsoft Intelligent Data Platform
ModelOp
New Relic
Omnisient
OpenAI
Slingshot
Superwise
Wizata

API Availability

Has API

API Availability

Has API

Pricing Information

$10 per month
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Featherless

Company Website

featherless.ai/

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/services/machine-learning/

Categories and Features

Categories and Features

Data Labeling

Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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