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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

We are excited to announce the launch of Phi-2, a language model featuring 2.7 billion parameters that excels in reasoning and language comprehension, achieving top-tier results compared to other base models with fewer than 13 billion parameters. In challenging benchmarks, Phi-2 competes with and often surpasses models that are up to 25 times its size, a feat made possible by advancements in model scaling and meticulous curation of training data. Due to its efficient design, Phi-2 serves as an excellent resource for researchers interested in areas such as mechanistic interpretability, enhancing safety measures, or conducting fine-tuning experiments across a broad spectrum of tasks. To promote further exploration and innovation in language modeling, Phi-2 has been integrated into the Azure AI Studio model catalog, encouraging collaboration and development within the research community. Researchers can leverage this model to unlock new insights and push the boundaries of language technology.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Airtrain No 
Axolotl No 
BERT Yes 
ChatGPT Yes 
Database Mart No 
Dolly Yes 
GPT-4 Yes 
LLaMA-Factory No 
LM-Kit.NET No 
Llama Yes 
Llama 2 Yes 
Llama 3.2 Yes 
Microsoft Azure No 
NativeMind No 
Oumi No 
Private LLM No 
Runpod No 
Stable LM Yes 
WeatherNext Yes 

Integrations

Airtrain Yes 
Axolotl Yes 
BERT No 
ChatGPT No 
Database Mart Yes 
Dolly No 
GPT-4 No 
LLaMA-Factory Yes 
LM-Kit.NET Yes 
Llama No 
Llama 2 No 
Llama 3.2 No 
Microsoft Azure Yes 
NativeMind Yes 
Oumi Yes 
Private LLM Yes 
Runpod Yes 
Stable LM No 
WeatherNext No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

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 Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
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 No 
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

Google DeepMind

Country

United States

Website

www.deepmind.com/blog/language-modelling-at-scale-gopher-ethical-considerations-and-retrieval

Vendor Details

Company Name

Microsoft

Founded

1975

Country

United States

Website

microsoft.com

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