Llama3-FFM

The first Traditional Chinese language model to achieve a TMMLU+ score that surpasses GPT-4.0 sets a new record for Traditional Chinese models!
Llama3-FFM is trained on Meta-Llama3 with an excellent Traditional Chinese corpus, featuring a native 128K multilingual extended vocabulary, powerful reasoning capabilities, and diverse application scenarios. In addition, the model has a Tool Call function, which can quickly connect to external information to expand comprehensive commercial applications.

Llama3-FFM

★ First Traditional Chinese model benchmark surpasses GPT-4.0 ★
★ Offers FFM large language model 70B/8B options ★
★ The Llama series has been fully upgraded, with significant improvements in all aspects of performance. ★
★ Supports Tool Call functionality for quick integration with external applications ★
★ Features a native 128K multilingual expanded vocabulary ★

Llama3-FFM surpasses GPT-4.0, setting a new record for Traditional Chinese models.

Applicable Scenarios

Strong reasoning and problem-solving skills

Llama3-FFM has demonstrated superior reasoning and problem-solving capabilities in multiple standardized evaluations (such as TMMLU+, MMLU, etc.), surpassing many similar models.

Diverse application scenarios

Llama3-FFM can be applied to multiple domain tasks, including NLP, coding, and complex logic question answering. Its rich training data and advanced model structure make it widely applicable to various domain scenarios.

Tool Call Function

It has the ability to quickly connect to external applications, such as Google Maps, search engines, transportation ticketing, and real-time financial stock price inquiries, making it easier for developers to enhance the model's capabilities and expand its commercial application possibilities.

Free Consultation Service

Contact Taiwan AI Cloud experts to learn about and start using the solution that suits you.

Customer Service & Technical Support

EDM Subscription

On-Demand AI Cloud Consulting

EDM Subscription

Sales Contact
Sales Contact Form