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Description
Oumi is an entirely open-source platform that enhances the complete lifecycle of foundation models, encompassing everything from data preparation and training to evaluation and deployment. It facilitates the training and fine-tuning of models with parameter counts ranging from 10 million to an impressive 405 billion, utilizing cutting-edge methodologies such as SFT, LoRA, QLoRA, and DPO. Supporting both text-based and multimodal models, Oumi is compatible with various architectures like Llama, DeepSeek, Qwen, and Phi. The platform also includes tools for data synthesis and curation, allowing users to efficiently create and manage their training datasets. For deployment, Oumi seamlessly integrates with well-known inference engines such as vLLM and SGLang, which optimizes model serving. Additionally, it features thorough evaluation tools across standard benchmarks to accurately measure model performance. Oumi's design prioritizes flexibility, enabling it to operate in diverse environments ranging from personal laptops to powerful cloud solutions like AWS, Azure, GCP, and Lambda, making it a versatile choice for developers. This adaptability ensures that users can leverage the platform regardless of their operational context, enhancing its appeal across different use cases.
Description
Strands Decider is a compact and swift decision-making model, known as a System One model, tailored for agentic AI applications. In contrast to a language model that produces random text, this model selects from a set of predefined options, responds to yes-or-no inquiries, or assesses inputs using an ordered scale. Each decision made by the Strands Decider is accompanied by a calibrated confidence score, enabling the efficient processing of routine decisions while allowing uncertain cases to be escalated to either a larger model or a human for further analysis. The initial iteration of this model, strands-decider-2B, comprises 1.9 billion parameters and is built upon the Qwen3.5-2B-Base architecture, featuring a streamlined pointer head in place of its language-modeling component. It performs evaluations in a single forward pass, eliminating the need for text generation or a decoding loop. Supported types of decisions encompass choice selections, noul for probability assessments, and score for evaluating ordered scales. This model is engineered for a variety of applications, including model routing, selecting tools, verifying tool arguments, triaging requests, establishing grounding and safety measures, classifying policies, and providing economical evaluations, thereby enhancing its utility in diverse AI workflows.
API Access
Has API
No
API Access
Has API
Yes
Integrations
AWS Lambda
Yes
Amazon Web Services (AWS)
Yes
DeepSeek
Yes
Google Cloud Platform
Yes
Llama
Yes
Microsoft Azure
Yes
Phi-2
Yes
Qwen
Yes
Strands Agents
No
Integrations
AWS Lambda
No
Amazon Web Services (AWS)
No
DeepSeek
No
Google Cloud Platform
No
Llama
No
Microsoft Azure
No
Phi-2
No
Qwen
No
Strands Agents
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
Yes
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Oumi
Founded
2024
Country
United States
Website
oumi.ai/
Vendor Details
Company Name
Strands Labs
Country
United States
Website
github.com/strands-labs/strands-decider