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app.py

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+# =========================================================
+# 1) INSTALL DEPENDENCIES
+# =========================================================
+!pip -q install git+https://github.com/huggingface/parler-tts.git
+!pip -q install soundfile transformers accelerate sentencepiece huggingface_hub
+
+# =========================================================
+# 2) IMPORTS
+# =========================================================
+import os
+import torch
+import soundfile as sf
+from IPython.display import Audio, display
+from google.colab import files
+from parler_tts import ParlerTTSForConditionalGeneration
+from transformers import AutoTokenizer
+from huggingface_hub import notebook_login, hf_hub_download
+
+# =========================================================
+# 3) HUGGING FACE LOGIN
+# =========================================================
+print("🔐 Please login with your Hugging Face READ token")
+notebook_login()
+
+# =========================================================
+# 4) VERIFY MODEL ACCESS
+# =========================================================
+MODEL_NAME = "ai4bharat/indic-parler-tts"
+
+try:
+    hf_hub_download(
+        repo_id=MODEL_NAME,
+        filename="config.json"
+    )
+    print("✅ Model access verified")
+except Exception as e:
+    print("❌ ACCESS ERROR")
+    print("Open this page:")
+    print("https://huggingface.co/ai4bharat/indic-parler-tts")
+    print("Then click 👉 Agree and access repository")
+    raise e
+
+# =========================================================
+# 5) DEVICE
+# =========================================================
+device = "cuda" if torch.cuda.is_available() else "cpu"
+print("🚀 Using device:", device)
+
+# =========================================================
+# 6) LOAD MODEL
+# =========================================================
+print("⏳ Loading Kannada TTS model...")
+model = ParlerTTSForConditionalGeneration.from_pretrained(
+    MODEL_NAME
+).to(device)
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+
+description_tokenizer = AutoTokenizer.from_pretrained(
+    model.config.text_encoder._name_or_path
+)
+
+print("✅ Model loaded successfully")
+
+# =========================================================
+# 7) SAFE GENERATION FUNCTION
+# =========================================================
+def generate_kannada_tts(prompt_text, output_file="/content/kannada_output.wav"):
+    prompt_text = str(prompt_text).strip()
+
+    if not prompt_text:
+        raise ValueError("❌ Kannada input cannot be empty")
+
+    description = (
+        "A calm Kannada male speaker with natural pronunciation, "
+        "clear studio quality audio, smooth narration, "
+        "and no background noise."
+    )
+
+    description_inputs = description_tokenizer(
+        description,
+        return_tensors="pt"
+    ).to(device)
+
+    prompt_inputs = tokenizer(
+        prompt_text,
+        return_tensors="pt"
+    ).to(device)
+
+    with torch.no_grad():
+        generation = model.generate(
+            input_ids=description_inputs.input_ids,
+            prompt_input_ids=prompt_inputs.input_ids
+        )
+
+    audio = generation.cpu().numpy().squeeze()
+
+    sf.write(
+        output_file,
+        audio,
+        model.config.sampling_rate
+    )
+
+    print(f"✅ Audio saved → {output_file}")
+    display(Audio(output_file))
+
+    return output_file
+
+# =========================================================
+# 8) USER INPUT OUTSIDE FUNCTION
+# =========================================================
+user_text = input("Enter Kannada text: ")
+
+# Example:
+# ನಮಸ್ಕಾರ, ನನ್ನ ಹೆಸರು ಅಥ್ಮಿಕ
+
+try:
+    output_path = generate_kannada_tts(user_text)
+except Exception as e:
+    print("❌ Error:", e)
+
+# =========================================================
+# 9) DOWNLOAD
+# =========================================================
+if os.path.exists("/content/kannada_output.wav"):
+    files.download("/content/kannada_output.wav")

requirements.txt

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+gradio
+git+https://github.com/huggingface/parler-tts.git
+soundfile
+transformers
+accelerate
+sentencepiece
+torch