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加入LLAMA + 盘古 + RWKV本地模型

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binary-husky 2023-05-05 04:31:31 +08:00 committed by GitHub
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docker-compose.yml
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@ -72,3 +72,46 @@ services:
bash -c " echo '[gpt-academic] 正在从github拉取最新代码...' &&
git pull &&
python3 -u main.py"
### ===================================================
### 【方案三】 如果需要运行ChatGPT + LLAMA + 盘古 + RWKV本地模型
### ===================================================
version: '3'
services:
gpt_academic_with_rwkv:
image: fuqingxu/gpt_academic:jittorllms # [option 2] 如果需要运行ChatGPT + LLAMA + 盘古 + RWKV本地模型
environment:
# 请查阅 `config.py` 以查看所有的配置信息
API_KEY: ' sk-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx,fkxxxxxx-xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx '
USE_PROXY: ' True '
proxies: ' { "http": "socks5h://localhost:10880", "https": "socks5h://localhost:10880", } '
LLM_MODEL: ' gpt-3.5-turbo '
AVAIL_LLM_MODELS: ' ["gpt-3.5-turbo", "api2d-gpt-4", "newbing", "jittorllms_rwkv", "jittorllms_llama", "jittorllms_pangualpha"] '
LOCAL_MODEL_DEVICE: ' cuda '
DEFAULT_WORKER_NUM: ' 10 '
WEB_PORT: ' 32303 '
ADD_WAIFU: ' True '
AUTHENTICATION: ' [("username", "passwd"), ("username2", "passwd2")] '
# 显卡的使用，nvidia0指第0个GPU
runtime: nvidia
devices:
- /dev/nvidia0:/dev/nvidia0
# 与宿主的网络融合
network_mode: "host"
# 使用代理网络拉取最新代码
# command: >
# bash -c " echo '[gpt-academic] 正在从github拉取最新代码...' &&
# truncate -s -1 /etc/proxychains.conf &&
# echo \"socks5 127.0.0.1 10880\" >> /etc/proxychains.conf &&
# proxychains git pull &&
# python3 -u main.py "
# 不使用代理网络拉取最新代码
command: >
bash -c " echo '[gpt-academic] 正在从github拉取最新代码...' &&
git pull &&
python3 -u main.py"