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app.py

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+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from snac import SNAC
+import soundfile as sf
+import gradio as gr
+
+# Load models
+model = AutoModelForCausalLM.from_pretrained(
+    "maya-research/maya1",
+    torch_dtype=torch.bfloat16,
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained("maya-research/maya1")
+snac_model = SNAC.from_pretrained("hubertsiuzdak/snac_24khz").eval().to("cuda")
+
+# Main generation function
+def generate_voice(description, text):
+    prompt = f'<description="{description}"> {text}'
+    inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
+    with torch.inference_mode():
+        outputs = model.generate(
+            **inputs,
+            max_new_tokens=500,
+            temperature=0.4,
+            top_p=0.9,
+            do_sample=True
+        )
+
+    generated_ids = outputs[0, inputs['input_ids'].shape[1]:]
+    snac_tokens = [t.item() for t in generated_ids if 128266 <= t <= 156937]
+
+    frames = len(snac_tokens) // 7
+    codes = [[], [], []]
+    for i in range(frames):
+        s = snac_tokens[i*7:(i+1)*7]
+        codes[0].append((s[0]-128266) % 4096)
+        codes[1].extend([(s[1]-128266) % 4096, (s[4]-128266) % 4096])
+        codes[2].extend([(s[2]-128266) % 4096, (s[3]-128266) % 4096,
+                         (s[5]-128266) % 4096, (s[6]-128266) % 4096])
+
+    codes_tensor = [torch.tensor(c, dtype=torch.long, device="cuda").unsqueeze(0) for c in codes]
+    with torch.inference_mode():
+        audio = snac_model.decoder(snac_model.quantizer.from_codes(codes_tensor))[0, 0].cpu().numpy()
+
+    out_path = "output.wav"
+    sf.write(out_path, audio, 24000)
+    return out_path
+
+# Gradio interface — no preset text, fully user-controlled
+demo = gr.Interface(
+    fn=generate_voice,
+    inputs=[
+        gr.Textbox(label="Voice Description (e.g., calm female voice with British accent)"),
+        gr.Textbox(label="Text to Speak (type anything you want)")
+    ],
+    outputs=gr.Audio(label="Generated Speech"),
+    title="🎙️ Maya1 Voice Generator",
+    description="Generate expressive emotional speech using the open-source Maya1 + SNAC pipeline."
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

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+torch
+transformers
+soundfile
+snac
+gradio