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What is OPT?

Large language models, which often demand significant computational power and prolonged training periods, have shown remarkable abilities in performing zero- and few-shot learning tasks. The substantial resources required for their creation make it quite difficult for many researchers to replicate these models. Moreover, access to the limited number of models available through APIs is restricted, as users are unable to acquire the full model weights, which hinders academic research. To address these issues, we present Open Pre-trained Transformers (OPT), a series of decoder-only pre-trained transformers that vary in size from 125 million to 175 billion parameters, which we aim to share fully and responsibly with interested researchers. Our research reveals that OPT-175B achieves performance levels comparable to GPT-3, while consuming only one-seventh of the carbon emissions needed for GPT-3's training process. In addition to this, we plan to offer a comprehensive logbook detailing the infrastructural challenges we faced during the project, along with code to aid experimentation with all released models, ensuring that scholars have the necessary resources to further investigate this technology. This initiative not only democratizes access to advanced models but also encourages sustainable practices in the field of artificial intelligence.

What is Azure OpenAI Service?

Leverage advanced coding and linguistic models across a wide range of applications. Tap into the capabilities of extensive generative AI models that offer a profound understanding of both language and programming, facilitating innovative reasoning and comprehension essential for creating cutting-edge applications. These models find utility in various areas, such as writing assistance, code generation, and data analytics, all while adhering to responsible AI guidelines to mitigate any potential misuse, supported by robust Azure security measures. Utilize generative models that have been exposed to extensive datasets, enabling their use in multiple contexts like language processing, coding assignments, logical reasoning, inferencing, and understanding. Customize these generative models to suit your specific requirements by employing labeled datasets through an easy-to-use REST API. You can improve the accuracy of your outputs by refining the model’s hyperparameters and applying few-shot learning strategies to provide the API with examples, resulting in more relevant outputs and ultimately boosting application effectiveness. By implementing appropriate configurations and optimizations, you can significantly enhance your application's performance while ensuring a commitment to ethical practices in AI application. Additionally, the continuous evolution of these models allows for ongoing improvements, keeping pace with advancements in technology.

Media

No images available

Media

Integrations Supported

Aim
Azure AI Search
ChatKit
CodeNext
EarlyCore
GPT-5.1 Instant
GPT-5.2 Pro
GPT-5.6
Jitterbit
Langtail
LiteLLM
Microsoft Azure
Microsoft Intelligent Data Platform
Motific.ai
OpenAI
Opik
Pendula
Sourcebot
String.com
ZenML

Integrations Supported

Aim
Azure AI Search
ChatKit
CodeNext
EarlyCore
GPT-5.1 Instant
GPT-5.2 Pro
GPT-5.6
Jitterbit
Langtail
LiteLLM
Microsoft Azure
Microsoft Intelligent Data Platform
Motific.ai
OpenAI
Opik
Pendula
Sourcebot
String.com
ZenML

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$0.0004 per 1000 tokens
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

Meta

Date Founded

2004

Company Location

United States

Company Website

www.meta.com

Company Facts

Organization Name

Microsoft

Date Founded

1975

Company Location

United States

Company Website

azure.microsoft.com/en-us/products/cognitive-services/openai-service

Categories and Features

Categories and 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)

Natural Language Generation

Business Intelligence
CRM Data Analysis and Reports
Chatbot
Email Marketing
Financial Reporting
Multiple Language Support
SEO
Web Content

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

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