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Description

Chinchilla is an advanced language model that operates with a compute budget comparable to Gopher while having 70 billion parameters and utilizing four times the amount of data. This model consistently and significantly surpasses Gopher (280 billion parameters), as well as GPT-3 (175 billion), Jurassic-1 (178 billion), and Megatron-Turing NLG (530 billion), across a wide variety of evaluation tasks. Additionally, Chinchilla's design allows it to use significantly less computational power during the fine-tuning and inference processes, which greatly enhances its applicability in real-world scenarios. Notably, Chinchilla achieves a remarkable average accuracy of 67.5% on the MMLU benchmark, marking over a 7% enhancement compared to Gopher, showcasing its superior performance in the field. This impressive capability positions Chinchilla as a leading contender in the realm of language models.

Description

OpenEuroLLM represents a collaborative effort between prominent AI firms and research organizations across Europe, aimed at creating a suite of open-source foundational models to promote transparency in artificial intelligence within the continent. This initiative prioritizes openness by making data, documentation, training and testing code, and evaluation metrics readily available, thereby encouraging community participation. It is designed to comply with European Union regulations, with the goal of delivering efficient large language models that meet the specific standards of Europe. A significant aspect of the project is its commitment to linguistic and cultural diversity, ensuring that multilingual capabilities cover all official EU languages and potentially more. The initiative aspires to broaden access to foundational models that can be fine-tuned for a range of applications, enhance evaluation outcomes across different languages, and boost the availability of training datasets and benchmarks for researchers and developers alike. By sharing tools, methodologies, and intermediate results, transparency is upheld during the entire training process, fostering trust and collaboration within the AI community. Ultimately, OpenEuroLLM aims to pave the way for more inclusive and adaptable AI solutions that reflect the rich diversity of European languages and cultures.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

No images available

Screenshots View All

Integrations

Google Stitch Yes 
MusicFX Yes 
WeatherNext Yes 

Integrations

Google Stitch No 
MusicFX 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 Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
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 No 

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

Google DeepMind

Country

United States

Website

arxiv.org/abs/2203.15556

Vendor Details

Company Name

OpenEuroLLM

Website

openeurollm.eu/

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