初始化项目，由ModelHub XC社区提供模型

Model: malaysia-ai/Qwen3-1.7B-Multilingual-TTS
Source: Original Platform

README.md

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+---
+library_name: transformers
+datasets:
+- malaysia-ai/Multilingual-TTS
+- malaysia-ai/Emilia-YODAS-Voice-Conversion
+- mesolitica/Malaysian-Emilia-v2
+base_model:
+- Qwen/Qwen3-1.7B-Base
+new_version: Scicom-intl/Multilingual-TTS-1.7B-Base
+---
+
+# Qwen3-1.7B-Multilingual-TTS
+
+Continue pretraining [Qwen/Qwen3-1.7B-Base](https://huggingface.co/Qwen/Qwen3-1.7B-Base) on Multilingual Voice Conversion and TTS.
+
+1. Use [neucodec](https://huggingface.co/neuphonic/neucodec) as speech detokenizer, 50 TPS, output in 24k sample rate.
+2. Multi-speaker multilingual Voice Conversion **up to 25.5B tokens**.
+3. Multi-speaker multilingual TTS up to **5B tokens**.
+4. Flash Attention 3 10k context length multipacking.
+5. Liger Kernel for `swiglu`, `rms_norm` and `fused_linear_cross_entropy`.
+   
+WanDB at https://wandb.ai/huseinzol05/Qwen-Qwen3-1.7B-Base-multilingual-tts-neucodec
+
+**We released better version at [Scicom-intl/Multilingual-TTS-1.7B-Base](https://huggingface.co/Scicom-intl/Multilingual-TTS-1.7B-Base)**.
+
+## How to
+
+```python
+import soundfile as sf
+import torch
+import torchaudio
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from neucodec import NeuCodec
+import re
+
+model_name = "malaysia-ai/Qwen3-1.7B-Multilingual-TTS"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype="auto").to('cuda')
+codec = NeuCodec.from_pretrained("neuphonic/neucodec")
+_ = codec.eval().to('cuda')
+```
+
+## TTS
+
+```python
+text = "Hello! how come I help you? 你好！有什么可以帮你的吗？வணக்கம்! நான் உங்களுக்கு எப்படி உதவுவது? Bonjour! Comment puis-je vous aider ? Xin chào! Tôi có thể giúp gì cho bạn? こんにちは！どうしてお手伝いしましょうか？안녕하세요! 어떻게 도와드릴까요?"
+prompt = f"<|im_start|>jenny_tts_dataset_audio_jenny: {text}<|speech_start|>"
+
+inputs = tokenizer(prompt,return_tensors="pt", add_special_tokens=True).to('cuda')
+
+with torch.no_grad():
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=2048,
+        do_sample=True,
+        temperature=0.6,
+        repetition_penalty=1.15,
+    )
+
+generated_text = tokenizer.decode(outputs[0], skip_special_tokens=False)
+audio_tokens = re.findall(r'<\|s_(\d+)\|>', generated_text.split('<|speech_start|>')[1])
+audio_tokens = [int(token) for token in audio_tokens]
+audio_codes = torch.tensor(audio_tokens)[None, None]
+
+with torch.no_grad():
+    audio_waveform = codec.decode_code(audio_codes.cuda())
+
+sf.write('7-languages.mp3', audio_waveform[0, 0].cpu(), 24000)
+```
+
+You can check the audio [7-languages.mp3](7-languages.mp3).
+
+- You can pick any speaker name from [malaysia-ai/Multilingual-TTS](malaysia-ai/Multilingual-TTS).
+- **Not bad from 0.35 epoch model**.
+
+### Voice Conversion
+
+```python
+import librosa
+
+y, sr = librosa.load('jenny.wav', sr = 16000)
+with torch.no_grad():
+    codes = codec.encode_code(torch.tensor(y)[None, None])
+tokens = ''.join([f'<|s_{i}|>' for i in codes[0, 0]])
+prompt = f"<|im_start|>I wonder if I shall ever be happy enough to have real lace on my clothes and bows on my caps.<|speech_start|>{tokens}<|im_end|><|im_start|>Hello, how come I help you, 你好, 有什么可以帮你的吗, வணக்கம், நான் உங்களுக்கு எப்படி உதவுவது, bonjour, comment puis-je vous aider.<|speech_start|>"
+
+inputs = tokenizer(prompt,return_tensors="pt", add_special_tokens=True).to('cuda')
+
+with torch.no_grad():
+    outputs = model.generate(
+        **inputs,
+        max_new_tokens=2048,
+        do_sample=True,
+        temperature=0.6,
+        repetition_penalty=1.15,
+    )
+
+generated_text = tokenizer.decode(outputs[0], skip_special_tokens=False)
+audio_tokens = re.findall(r'<\|s_(\d+)\|>', generated_text.split('<|speech_start|>')[-1])
+audio_tokens = [int(token) for token in audio_tokens]
+audio_codes = torch.tensor(audio_tokens)[None, None]
+
+with torch.no_grad():
+    audio_waveform = codec.decode_code(audio_codes.cuda())
+
+sf.write('jenny-4-languages.mp3', audio_waveform[0, 0].cpu(), 24000)
+```
+
+You can check the audio [jenny-4-languages.mp3](jenny-4-languages.mp3).
+
+- **Not too great, we need to trim the silents first before convert to audio tokens, the model tends to generate long silents**.
+
+## Source code
+
+Source code at https://github.com/malaysia-ai/cooking/tree/main/qwen-tts