license: gpl-3.0
BayLing: Bridging Cross-lingual Alignment and Instruction Following through Interactive Translation for Large Language Models
BayLing (百聆, bǎi líng) is an instruction-following LLM equipped with advanced language alignment, showing superior capability in English/Chinese generation, instruction following and multi-turn interaction. BayLing can be effortlessly deployed on a consumer-grade GPU with 16GB of memory, and assists users with tasks such as translation, writing, creation, suggestion...
This model is the weight-diff version of BayLing-7B.
👇 Learn more about BayLing:
💬 Demo: Welcome to apply for a trial of BayLing's online demo (beta version).
📄 Paper: BayLing's technical report.
🏠 Blog: BayLing's homepage. You can discover some case of BayLing here.
✍️ BayLing-80 Test Set: A human-annotated evaluation set comprising multi-turn instructions in both English and Chinese, can be used to evaluate the multilingual and multi-turn interaction capabilities of LLMs.
🤗 Model: The weight-diff version of BayLing-7B and BayLing-13B, you can quickly get the parameters of BayLing through apply_delta.py. The HF models of BayLing are anonymized version (exclude BayLing's name in its knowledge), in order to facilitate future LLMs to build upon BayLing.
BayLing is developed by NLP Group of Institute of Computing Technology, Chinese Academy of Sciences (ICT/CAS)
Any question or suggestion, please contact with
[email protected]
Refer to our Github Repo for the detailed introduction to BayLing, including deploying BayLing, interacting with BayLing and BayLing's performance.