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app.py

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+import torch
+from parler_tts import ParlerTTSForConditionalGeneration
+from transformers import AutoTokenizer, AutoFeatureExtractor
+import gradio as gr
+import spaces
+
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+
+model_name = "parler-tts/parler_tts_mini_v0.1"
+
+model = ParlerTTSForConditionalGeneration.from_pretrained(model_name).to(device)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+feature_extractor = AutoFeatureExtractor.from_pretrained(model_name)
+
+sr = feature_extractor.sampling_rate
+
+examples = [
+    [
+        "Hey, how are you doing today?",
+        "A female speaker with a slightly high-pitched voice delivers her words quite expressively, in a very confined sounding environment with clear audio quality. She speaks very fast."
+    ],
+    [
+        "The life of the land is perpetuated in righteousness.",
+        "A male speaker with a low-pitched voice delivers his words at a slightly slow pace and a dramatic tone, in a very spacious environment, accompanied by noticeable background noise."
+    ]
+]
+
+@spaces.GPU
+def generate_speech(text, description):
+    """
+    Generate speech with a text prompt.
+    """
+    input_ids = tokenizer(description, return_tensors="pt").input_ids.to(device)
+    prompt_input_ids = tokenizer(text, return_tensors="pt").input_ids.to(device)
+    
+    generation = model.generate(
+        input_ids=input_ids,
+        prompt_input_ids=prompt_input_ids,
+        do_sample=True,
+        temperature=1.0
+    )
+    audio_arr = generation.cpu().numpy().squeeze()
+    
+    return sr, audio_arr
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Parler-TTS Mini")
+    gr.Markdown(
+        """
+        Tips:
+        - Include term "very clear audio" and/or "very noisy audio"
+        - Use punctuation for prosody
+        - Control gender, speaking rate, pitch, reverberation in prompt
+        """
+    )
+    with gr.Row():
+        with gr.Column():
+            input_text = gr.Textbox(
+                label="Input Text",
+                lines=2,
+                elem_id="input_text"
+            )
+            description = gr.Textbox(
+                label="Description",
+                lines=2,
+                elem_id="input_description"
+            )
+            run_button = gr.Button("Generate Audio", variant="primary")
+        with gr.Column():
+            audio_out = gr.Audio(
+                label="Parler-TTS generation",
+                type="numpy",
+                elem_id="audio_out"
+            )
+    
+    inputs = [input_text, description]
+    outputs = [audio_out]
+    gr.Examples(
+        examples=examples,
+        fn=generate_speech,
+        inputs=inputs,
+        outputs=outputs,
+        cache_examples=True
+    )
+    run_button.click(
+        fn=generate_speech,
+        inputs=inputs,
+        outputs=outputs,
+        queue=True
+    )
+
+demo.queue()
+
+demo.launch()

requirements.txt

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+git+https://github.com/huggingface/parler-tts.git
+gradio
+spaces