metadata
license: creativeml-openrail-m
language:
- en
tags:
- LLM
- BELLE
Model Card for lyraBELLE
lyraBELLE is currently the fastest BELLE model available. To the best of our knowledge, it is the first accelerated version of BELLE.
The inference speed of lyraBELLE has achieved 100x acceleration upon the original version.
Among its main features are:
- weights: the original BELLE-7B-2M weights released by BelleGroup.
- device: Nvidia Ampere architechture or newer (e.g A100)
Note that: Some interface/code were set for future uses(see demo below).
- int8 mode: not supported yet, please always set it to 0
- data type: only
fp16
available.
Speed
test environment
- device: Nvidia A100 40G
- warmup: 10 rounds
- percision:fp16
- batch size for our version: 64 (maximum under A100 40G)
- batch size for original: xx (maximum under A100 40G)
|version|batch size|speed| |:-:|:-:| |original|xxx| |lyraBELLE|80|3030.36 tokens/sec|
Model Sources
Environment
- docker image available at [https://hub.docker.com/repository/docker/bigmoyan/lyrallm/general], pull image by:
docker pull bigmoyan/lyrallm:v0.1
Uses
from lyraBelle import LyraBelle
data_type = "fp16"
prompts = "今天天气大概 25度,有点小雨,吹着风,我想去户外散步,应该穿什么样的衣服裤子鞋子搭配。"
model_dir = "./model"
model_name = "1-gpu-fp16.h5"
max_output_length = 512
# int8 mode not supported, data_type only support fp16
model = LyraBelle(model_dir, model_name, data_type, 0)
output_texts = model.generate(prompts, output_length=max_output_length,top_k=30, top_p=0.85, temperature=0.35, repetition_penalty=1.2, do_sample=True)
print(output_texts)
Demo output
input
今天天气大概 25度,有点小雨,吹着风,我想去户外散步,应该穿什么样的衣服裤子鞋子搭配。
output
建议穿着一件轻便的衬衫或T恤、一条牛仔裤和一双运动鞋或休闲鞋。如果下雨了可以带上一把伞。
Citation
@Misc{lyraBELLE2023,
author = {Kangjian Wu, Zhengtao Wang, Bin Wu},
title = {lyraBELLE: Accelerating BELLE by 100x+},
howpublished = {\url{https://huggingface.co/TMElyralab/lyraBELLE},
year = {2023}
}
Report bug
- start a discussion to report any bugs!--> https://huggingface.co/TMElyralab/lyraBELLE/discussions
- report bug with a
[bug]
mark in the title.