T‑LLaMA: a Tibetan large language model based on LLaMA2

In this study, we built a corpus containing 2.2 billion Tibetan characters and trained Tibetan LLaMA based on LLaMA2 7B. We achieved state-of-the-art performance in the text classification task using the open-source TNCC dataset, with an accuracy of 79.8%. Additionally, we obtained promising results in text generation and text summarization tasks.

Downloads last month
50
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for Pagewood/T-LLaMA

Quantizations
1 model