Introduction

OpenBA is an Open-Sourced 15B Bilingual Asymmetric Seq2Seq Model Pre-trained from Scratch.

Open Source Plan

We are excited to unveil two distinguished versions of our model, with another on the horizon:

• OpenBA-LM: The backbone language models was pre-trained on 340B English, Chinese, and code tokens.
• OpenBA-Flan: We perform supervised fine-tuning on the base model with additional 40B tokens using our collected BiFlan Dataset.
• OpenBA-Chat: coming soon

Model Description

• Model type: Language model
• Language(s) (NLP): zh, en (We also offer the possibility for multilingual learning, by using a multilingual tokenizer.)
• License: Apache 2.0
• Resources for more information:
  • Paper
  • GitHub Repo

Usage

Install requirements

pip install transformers torch>=2.0 sentencepiece

Demo usage

>>> from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
>>> tokenizer = AutoTokenizer.from_pretrained("OpenBA/OpenBA-LM", trust_remote_code=True)
>>> model = AutoModelForSeq2SeqLM.from_pretrained("OpenBA/OpenBA-LM", trust_remote_code=True).half().cuda()
>>> model = model.eval()
>>> query = "<S>" + "苏州处太湖平原，沿江为高沙平原，河" + "<extra_id_0>"
>>> inputs = tokenizer(query, return_tensors="pt").to("cuda")
>>> outputs = model.generate(**inputs, do_sample=True, max_new_tokens=32)
>>> response = tokenizer.decode(outputs[0], skip_special_tokens=True)
>>> print(response)
流两侧为河淤平原,苏州平原是江苏平原主体,地势低平,土地肥沃,气候温和