74 lines
2.3 KiB
Python
74 lines
2.3 KiB
Python
from transformers import AutoModelForCausalLM, AutoTokenizer
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from cosyvoice.cli.cosyvoice import CosyVoice
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from cosyvoice.utils.file_utils import load_wav
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import torchaudio
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import pygame
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import time
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def play_audio(file_path):
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try:
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pygame.mixer.init()
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pygame.mixer.music.load(file_path)
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pygame.mixer.music.play()
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while pygame.mixer.music.get_busy():
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time.sleep(1) # 等待音频播放结束
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print("播放完成！")
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except Exception as e:
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print(f"播放失败: {e}")
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finally:
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pygame.mixer.quit()
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model_name = r"D:\AI\download\Qwen2.5-0.5B-Instruct"
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype="auto",
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device_map="auto"
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)
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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cosyvoice = CosyVoice(r'../pretrained_models/CosyVoice-300M', load_jit=True, load_onnx=False, fp16=True)
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# sft usage
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print(cosyvoice.list_avaliable_spks())
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prompt = "你好，你叫什么名字?"
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messages = [
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{"role": "system", "content": "You are Qwen, created by Alibaba Cloud. You are a helpful assistant."},
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{"role": "user", "content": prompt},
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]
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text = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True,
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)
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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generated_ids = model.generate(
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**model_inputs,
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max_new_tokens=512,
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)
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generated_ids = [
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output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
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]
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response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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print("Input:", prompt)
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print("Answer:", response)
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# ['中文女', '中文男', '日语男', '粤语女', '英文女', '英文男', '韩语女']
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for i, j in enumerate(cosyvoice.inference_sft(f'{prompt}', '中文男', stream=False)):
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torchaudio.save('prompt_sft_{}.wav'.format(i), j['tts_speech'], 22050)
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# play_audio('prompt_sft_{}.wav'.format(i))
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# change stream=True for chunk stream inference
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for i, j in enumerate(cosyvoice.inference_sft(f'{response}', '中文女', stream=False)):
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torchaudio.save('sft_{}.wav'.format(i), j['tts_speech'], 22050)
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# play_audio('sft_{}.wav'.format(i))
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play_audio('prompt_sft_0.wav')
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for i, j in enumerate(f'{response}'):
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play_audio('sft_{}.wav'.format(i))
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