Update README.md

README.md

@@ -9,4 +9,41 @@ Finetuned https://huggingface.co/parler-tts/parler-tts-mini-v1 on Malay TTS data
 
 Source code at https://github.com/mesolitica/malaya-speech/tree/master/session/parler-tts
 
-Wandb at https://wandb.ai/huseinzol05/parler-speech?nw=nwuserhuseinzol05
+Wandb at https://wandb.ai/huseinzol05/parler-speech?nw=nwuserhuseinzol05
+
+## how-to
+
+```python
+import torch
+from parler_tts import ParlerTTSForConditionalGeneration
+from transformers import AutoTokenizer
+import soundfile as sf
+
+device = "cuda:0" if torch.cuda.is_available() else "cpu"
+
+model = ParlerTTSForConditionalGeneration.from_pretrained("mesolitica/malay-parler-tts-mini-v1").to(device)
+tokenizer = AutoTokenizer.from_pretrained("mesolitica/malay-parler-tts-mini-v1")
+
+speakers = [
+    'Yasmin',
+    'Osman',
+    'Bunga',
+    'Ariff',
+    'Ayu',
+    'Kamarul',
+    'Danial',
+    'Elina',
+]
+
+prompt = 'Husein zolkepli sangat comel dan kacak suka makan cendol'
+
+for s in speakers:
+    description = f"{s}'s voice, delivers a slightly expressive and animated speech with a moderate speed and pitch. The recording is of very high quality, with the speaker's voice sounding clear and very close up."
+
+    input_ids = tokenizer(description, return_tensors="pt").input_ids.to(device)
+    prompt_input_ids = tokenizer(prompt, return_tensors="pt").input_ids.to(device)
+
+    generation = model.generate(input_ids=input_ids, prompt_input_ids=prompt_input_ids)
+    audio_arr = generation.cpu()
+    sf.write(f'{s}.mp3', audio_arr.numpy().squeeze(), 44100)
+```