Add application file

app.py

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+import gradio as gr
+from transformers import AutoProcessor, SeamlessM4Tv2Model
+import torch
+
+# 加载模型和处理器
+processor = AutoProcessor.from_pretrained("facebook/seamless-m4t-v2-large")
+model = SeamlessM4Tv2Model.from_pretrained("facebook/seamless-m4t-v2-large")
+
+
+
+
+def greet(text,src_lang,tgt_lang):
+    # 输入文本
+    text_inputs = processor(text=text, src_lang=src_lang, return_tensors="pt")
+    # 生成翻译的文本
+    output_tokens = model.generate(**text_inputs, tgt_lang=tgt_lang, generate_speech=False) 
+    translated_text_from_text = processor.decode(output_tokens[0].tolist()[0], skip_special_tokens=True)
+    return translated_text_from_text
+
+text = gr.Textbox(lines=5,label="输入文本",placeholder="请输入文本")
+src_lang = gr.Dropdown(label="源语言",choices=["en","zh"])
+tgt_lang = gr.Dropdown(label="目标语言",choices=["en","zh"])
+output_text = gr.Textbox(lines=5,label="翻译文本",placeholder="翻译文本")
+demo=gr.Interface(fn=greet, inputs=[text,src_lang,tgt_lang], outputs=output_text)
+demo.launch()

requirements.txt

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+sentencepiece
+git+https://github.com/huggingface/transformers.git
+torchaudio
+protobuf
+torch 
+torchvision 
+torchaudio