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What is mT5?

The multilingual T5 (mT5) is an exceptionally adaptable pretrained text-to-text transformer model, created using a methodology similar to that of the original T5. This repository provides essential resources for reproducing the results detailed in the mT5 research publication. mT5 has undergone training on the vast mC4 corpus, which includes a remarkable 101 languages, such as Afrikaans, Albanian, Amharic, Arabic, Armenian, Azerbaijani, Basque, Belarusian, Bengali, Bulgarian, Burmese, Catalan, Cebuano, Chichewa, Chinese, Corsican, Czech, Danish, Dutch, English, Esperanto, Estonian, Filipino, Finnish, French, Galician, Georgian, German, Greek, Gujarati, Haitian Creole, Hausa, Hawaiian, Hebrew, Hindi, Hmong, Hungarian, Icelandic, Igbo, Indonesian, Irish, Italian, Japanese, Javanese, Kannada, Kazakh, Khmer, Korean, Kurdish, Kyrgyz, Lao, Latin, Latvian, Lithuanian, Luxembourgish, Macedonian, Malagasy, Malay, Malayalam, Maltese, Maori, Marathi, Mongolian, Nepali, Norwegian, Pashto, Persian, Polish, Portuguese, Punjabi, Romanian, Russian, Samoan, Scottish Gaelic, Serbian, Shona, Sindhi, and many more. This extensive language coverage renders mT5 an invaluable asset for multilingual applications in diverse sectors, enhancing its usefulness for researchers and developers alike.

What is Llama?

Llama, a leading-edge foundational large language model developed by Meta AI, is designed to assist researchers in expanding the frontiers of artificial intelligence research. By offering streamlined yet powerful models like Llama, even those with limited resources can access advanced tools, thereby enhancing inclusivity in this fast-paced and ever-evolving field. The development of more compact foundational models, such as Llama, proves beneficial in the realm of large language models since they require considerably less computational power and resources, which allows for the exploration of novel approaches, validation of existing studies, and examination of potential new applications. These models harness vast amounts of unlabeled data, rendering them particularly effective for fine-tuning across diverse tasks. We are introducing Llama in various sizes, including 7B, 13B, 33B, and 65B parameters, each supported by a comprehensive model card that details our development methodology while maintaining our dedication to Responsible AI practices. By providing these resources, we seek to empower a wider array of researchers to actively participate in and drive forward the developments in the field of AI. Ultimately, our goal is to foster an environment where innovation thrives and collaboration flourishes.

Media

Media

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Integrations Supported

Admix
Agenta
Athina AI
Bolna
Concierge AI
Decopy AI
Featherless
Finestel
Jan
LLM Council
Llama 4 Behemoth
Locally AI
Overseer AI
PromptX
RankLLM
SurePath AI
ZeroGPT
amazee.ai
fullmoon
iMini

Integrations Supported

Admix
Agenta
Athina AI
Bolna
Concierge AI
Decopy AI
Featherless
Finestel
Jan
LLM Council
Llama 4 Behemoth
Locally AI
Overseer AI
PromptX
RankLLM
SurePath AI
ZeroGPT
amazee.ai
fullmoon
iMini

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
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

Google

Date Founded

1998

Company Location

United States

Company Website

github.com/google-research/multilingual-t5

Company Facts

Organization Name

Meta

Date Founded

2004

Company Location

United States

Company Website

www.llama.com

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