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Description
Language plays a crucial role in showcasing and enhancing understanding, which is essential to the human experience. It empowers individuals to share thoughts, convey ideas, create lasting memories, and foster empathy and connection with others. These elements are vital for social intelligence, which is why our teams at DeepMind focus on various facets of language processing and communication in both artificial intelligences and humans. Within the larger framework of AI research, we are convinced that advancing the capabilities of language models—systems designed to predict and generate text—holds immense promise for the creation of sophisticated AI systems. Such systems can be employed effectively and safely to condense information, offer expert insights, and execute commands through natural language. However, the journey toward developing beneficial language models necessitates thorough exploration of their possible consequences, including the challenges and risks they may introduce into society. By understanding these dynamics, we can work towards harnessing their power while minimizing any potential downsides.
Description
Large language models, often requiring extensive computational resources for training over long periods, have demonstrated impressive proficiency in zero- and few-shot learning tasks. Due to the high investment needed for their development, replicating these models poses a significant challenge for many researchers. Furthermore, access to the few models available via API is limited, as users cannot obtain the complete model weights, complicating academic exploration. In response to this, we introduce Open Pre-trained Transformers (OPT), a collection of decoder-only pre-trained transformers ranging from 125 million to 175 billion parameters, which we intend to share comprehensively and responsibly with interested scholars. Our findings indicate that OPT-175B exhibits performance on par with GPT-3, yet it is developed with only one-seventh of the carbon emissions required for GPT-3's training. Additionally, we will provide a detailed logbook that outlines the infrastructure hurdles we encountered throughout the project, as well as code to facilitate experimentation with all released models, ensuring that researchers have the tools they need to explore this technology further.
API Access
Has API
API Access
Has API
Screenshots View All
No images available
Integrations
BERT
ChatGPT
Dolly
GPT-4
Llama
Llama 2
Llama 3.1
Llama 3.2
Llama 3.3
Stable LM
Integrations
BERT
ChatGPT
Dolly
GPT-4
Llama
Llama 2
Llama 3.1
Llama 3.2
Llama 3.3
Stable LM
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
DeepMind
Founded
2010
Country
United Kingdom
Website
www.deepmind.com/blog/language-modelling-at-scale-gopher-ethical-considerations-and-retrieval
Vendor Details
Company Name
Meta
Founded
2004
Country
United States
Website
www.meta.com