gradio app

app.py

@@ -1,7 +1,36 @@
 import gradio as gr
+from transformers import BarkModel, AutoProcessor
+import torch
+from scipy.io.wavfile import write as write_wav
+import os
 
-def greet(name):
-    return "Hello " + name + "!!"
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+### if you run on GPU use the following code: ###
+# device = "cuda" if torch.cuda.is_available() else "cpu"
+# model = BarkModel.from_pretrained("suno/bark-small", torch_dtype=torch.float16).to(device)
+# model.enable_cpu_offload()
+
+### if you run on CPU use the following code: ###
+device = "cpu"
+# load in fp16
+model = BarkModel.from_pretrained("suno/bark-small").to(device)
+processor = AutoProcessor.from_pretrained("suno/bark")
+
+voice_preset = "v2/en_speaker_3"
+
+def generate_audio(text, preset, output_file_name="bark_generation"):
+    file_name = output_file_name + ".wav"
+    inputs = processor(text, voice_preset=preset)
+    audio_array = model.generate(**inputs)
+    audio_array = audio_array.cpu().numpy().squeeze()   
+    sample_rate = model.generation_config.sample_rate
+    write_wav(file_name, sample_rate, audio_array)
+    return file_name
+
+
+#Bark Presets List
+presets = ["v2/en_speaker_0","v2/en_speaker_1", "v2/en_speaker_2", "v2/en_speaker_3",  "v2/en_speaker_4",  "v2/en_speaker_5",  "v2/en_speaker_6"]
+
+#Gradio Interface
+iface = gr.Interface(fn=generate_audio, inputs=["text", gr.components.Dropdown(choices=presets), "text"], outputs="audio")
 iface.launch()

requirements.txt

@@ -1 +1,5 @@
 gradio
+transformers
+torch
+accelerate
+scipy