llm-asr-tts/4_Inference_QWen2Audio.py
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2025-03-17 00:41:41 +08:00

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Python

from io import BytesIO
from urllib.request import urlopen
import librosa
from transformers import Qwen2AudioForConditionalGeneration, AutoProcessor
model_name = r".\QWen\Qwen2-Audio-7B-Instruct"
processor = AutoProcessor.from_pretrained(model_name)
model = Qwen2AudioForConditionalGeneration.from_pretrained(model_name, device_map="cuda")
# conversation = [
# {"role": "user", "content": [
# {"type": "audio", "audio_url": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2-Audio/audio/guess_age_gender.wav"},
# ]},
# {"role": "assistant", "content": "Yes, the speaker is female and in her twenties."},
# {"role": "user", "content": [
# {"type": "audio", "audio_url": "https://qianwen-res.oss-cn-beijing.aliyuncs.com/Qwen2-Audio/audio/translate_to_chinese.wav"},
# ]},
# ]
# 定义对话
conversation = [
{"role": "user", "content": [
{"type": "audio", "audio_path": r".\QWen\Qwen2-Audio-7B-Instruct\guess_age_gender.wav"},
]},
{"role": "assistant", "content": "Yes, the speaker is female and in her twenties."},
{"role": "user", "content": [
{"type": "audio", "audio_path": r".\QWen\Qwen2-Audio-7B-Instruct\translate_to_chinese.wav"},
]},
]
text = processor.apply_chat_template(conversation, add_generation_prompt=True, tokenize=False)
audios = []
for message in conversation:
if isinstance(message["content"], list):
for ele in message["content"]:
if ele["type"] == "audio":
audios.append(librosa.load(
BytesIO(urlopen(ele['audio_url']).read()),
sr=processor.feature_extractor.sampling_rate)[0]
)
inputs = processor(text=text, audios=audios, return_tensors="pt", padding=True)
inputs.input_ids = inputs.input_ids.to("cuda")
generate_ids = model.generate(**inputs, max_length=256)
generate_ids = generate_ids[:, inputs.input_ids.size(1):]
response = processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
print("Answer:", response)