82 lines
2.7 KiB
Python
82 lines
2.7 KiB
Python
"""
|
||
This code is supported by the website: https://www.guanjihuan.com
|
||
The newest version of this code is on the web page: https://www.guanjihuan.com/archives/38502
|
||
"""
|
||
|
||
import streamlit as st
|
||
st.set_page_config(
|
||
page_title="Chat",
|
||
layout='wide'
|
||
)
|
||
|
||
choose_load_method = 1
|
||
|
||
if choose_load_method == 0:
|
||
# GPU加载（需要5G显存）
|
||
@st.cache_resource
|
||
def load_bark_model():
|
||
from transformers import AutoProcessor, AutoModel
|
||
processor = AutoProcessor.from_pretrained("suno/bark")
|
||
model = AutoModel.from_pretrained("suno/bark").to("cuda")
|
||
return model, processor
|
||
model, processor = load_bark_model()
|
||
|
||
elif choose_load_method == 1:
|
||
# GPU加载bark-small模型（需要3G显存）
|
||
@st.cache_resource
|
||
def load_bark_model():
|
||
from transformers import AutoProcessor, AutoModel
|
||
processor = AutoProcessor.from_pretrained("suno/bark-small")
|
||
model = AutoModel.from_pretrained("suno/bark-small").to("cuda")
|
||
return model, processor
|
||
model, processor = load_bark_model()
|
||
|
||
elif choose_load_method == 2:
|
||
# CPU加载bark模型（需要9G内存，运行速度慢，不推荐）
|
||
@st.cache_resource
|
||
def load_bark_model():
|
||
from transformers import AutoProcessor, AutoModel
|
||
processor = AutoProcessor.from_pretrained("suno/bark")
|
||
model = AutoModel.from_pretrained("suno/bark")
|
||
return model, processor
|
||
model, processor = load_bark_model()
|
||
|
||
elif choose_load_method == 3:
|
||
# CPU加载bark-small模型（需要5G内存，运行速度慢，不推荐）
|
||
@st.cache_resource
|
||
def load_bark_model():
|
||
from transformers import AutoProcessor, AutoModel
|
||
processor = AutoProcessor.from_pretrained("suno/bark-small")
|
||
model = AutoModel.from_pretrained("suno/bark-small")
|
||
return model, processor
|
||
model, processor = load_bark_model()
|
||
|
||
prompt = st.chat_input("在这里输入您的命令")
|
||
|
||
prompt_placeholder = st.empty()
|
||
with prompt_placeholder.container():
|
||
with st.chat_message("user", avatar='user'):
|
||
pass
|
||
|
||
if prompt:
|
||
with prompt_placeholder.container():
|
||
with st.chat_message("user", avatar='user'):
|
||
st.write(prompt)
|
||
st.write('正在转换中，请稍后。')
|
||
|
||
inputs = processor(
|
||
text=[prompt],
|
||
return_tensors="pt",
|
||
)
|
||
if choose_load_method == 0 or choose_load_method == 1:
|
||
inputs = {key: value.to("cuda") for key, value in inputs.items()}
|
||
|
||
speech_values = model.generate(**inputs, do_sample=True)
|
||
|
||
import scipy
|
||
sampling_rate = 24_000
|
||
scipy.io.wavfile.write('./a.wav', rate=sampling_rate, data=speech_values.cpu().numpy().squeeze())
|
||
|
||
audio_file = open('./a.wav', 'rb')
|
||
audio_bytes = audio_file.read()
|
||
st.audio(audio_bytes, format='audio/wav') |