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System One

Feishu Message Classification Benchmark

A frozen 64-case benchmark of Feishu-style workplace messages, scoring Jev and Laya on a single choice question and on a four-question workflow. Jev scored 100 and 98.44 percent correct, Laya scored 31.25 and 28.12 percent, on the same requests.

Feishu 消息分类成绩图,3:4 竖版
Image from github.com

Adkid-Zephyr/chinese-workflow-decision-bench on GitHub

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Language
Python
License
MIT
Last push
21 Sep 2026

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How it uses Jev

 client=httpx.Client(headers={'Authorization':'Bearer '+key.strip()},timeout=60);key=None
 metadata['model']='jev-1.13.0';metadata['httpx']=httpx.__version__
 def call(req):
  start=time.perf_counter();response=client.post('https://api.typesafe.ai/v1/systemone',json={**req,'model':'jev-1.13.0'})
  if response.status_code!=200:raise RuntimeError('HTTP '+str(response.status_code))
  result=response.json();ms=(time.perf_counter()-start)*1000
  return {k:result[k] for k in ['model','answers','usage'] if k in result},ms,{}
else:
 if not args.checkpoint:raise SystemExit('--checkpoint must point to a locally downloaded multilingual checkpoint')
 os.environ.update(HF_HUB_OFFLINE='1',USE_TF='0',USE_TORCH='1',TOKENIZERS_PARALLELISM='false')
 import torch,transformers,laya
 from laya.common import build_sequence,serialize_state
 torch.set_num_threads(2);start=time.perf_counter();model=laya.load(args.checkpoint,device=args.device)
 metadata.update(model='convaiinnovations/laya/multilingual',checkpoint_revision='1c5edc17a7acd8701df6fc341c0d179f1c62c982',checkpoint_config=model.cfg,load_seconds=time.perf_counter()-start,torch=torch.__version__,transformers=transformers.__version__,device=str(model.device),cpu_threads=2,hardware='Apple M4 MacBook Air, 32 GB unified memory',laya_source_commit='ef7d7d269e2e34c763c228144dc10fe7d421acf9')
 def call(req):

View in bench.py

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