Create app.py

app.py

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+import gradio as gr
+
+import torch
+from transformers import BarkModel
+from optimum.bettertransformer import BetterTransformer
+
+bark_model = BarkModel.from_pretrained("suno/bark", torch_dtype=torch.float16)
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+bark_model = bark_model.to(device)
+
+from transformers import AutoProcessor
+processor = AutoProcessor.from_pretrained("suno/bark")
+
+# Use bettertransform for flash attention
+bark_model = BetterTransformer.transform(bark_model, keep_original_model=False)
+
+# Enable CPU offload
+bark_model.enable_cpu_offload()
+
+from TTS.tts.configs.bark_config import BarkConfig
+from TTS.tts.models.bark import Bark
+
+config = BarkConfig()
+model = Bark.init_from_config(config)
+model.load_checkpoint(config, checkpoint_dir=bark_model, eval=True)
+
+def infer(prompt):
+
+    text = "Hello, my name is Manmay , how are you?"
+
+    # with random speaker
+    output_dict = model.synthesize(text, config, speaker_id="random", voice_dirs=None)
+
+    return "done"
+
+gr.Interface(fn=infer, inputs=[gr.Textbox()], outputs=[gr.Textbox()]).launch()