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)