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import os, asyncio
# import pickle
import discord
from discord.ext import commands
from dotenv import load_dotenv
from threading import Thread
from rwkvstic.load import RWKV
from rwkvstic.agnostic.backends import TORCH
import torch
load_dotenv()
bot = commands.Bot("", intents=discord.Intents.all())
# model_pipe = pickle.load(open('pipe.pkl', 'rb'))
# this is the dtype used for trivial operations, such as vector->vector operations and is the dtype that will determine the accuracy of the model
runtimedtype = torch.float16 # torch.float64, torch.bfloat16
# this is the dtype used for matrix-vector operations, and is the dtype that will determine the performance and memory usage of the model
dtype = torch.bfloat16 # torch.float32, torch.float64, torch.bfloat16
useGPU = torch.cuda.is_available() # False
@bot.event
async def on_ready():
print(f'We have logged in as {bot.user}')
global model
model = RWKV("RWKV-4-Pile-3B-Instruct-test2-20230209.pth",
mode=TORCH,
useGPU=useGPU,
runtimedtype=runtimedtype,
dtype=dtype)
@bot.listen('on_message')
async def on_message_event(message):
if message.author == bot.user:
return
if message.content.startswith("!rwkv "):
mess = await message.channel.send("Loading...")
model.resetState()
model.loadContext(
newctx=f"\n\nQuestion: {message.content[6:]}\n\nExpert Long Detailed Response: ")
tex = ""
for i in range(10):
print(i)
curr = model.forward(number=10)[
"output"]
tex = tex + curr
print(curr)
if ("<|endoftext|>" in curr):
break
mess = await mess.edit(content=tex)
await asyncio.sleep(1)
await mess.edit(content=tex)
# if message.content:
# print(message.content)
# # await message.channel.send(model_pipe.predict([message.content]))
# await message.channel.send('Hello from hugging face')
# await bot.process_commands(message)
bot.env = "prod" # type: ignore
bot.name = "testAniPin" # type: ignore
# t = Thread(target=bot.run, daemon=True, args=(os.getenv("discord_token"), ))
bot.run(os.getenv("discord_token"))
# t.start()
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