Text-to-Speech
ONNX
Transformers
PyTorch
Vietnamese
English
onnxruntime
tts
vietnamese
bilingual
zero-shot-cloning
code-switching
high-fidelity
onnxruntime-genai
Instructions to use haydso/VieNeu-TTS-v2-Turbo-ONNX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use haydso/VieNeu-TTS-v2-Turbo-ONNX with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-speech", model="haydso/VieNeu-TTS-v2-Turbo-ONNX")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("haydso/VieNeu-TTS-v2-Turbo-ONNX", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "model": { | |
| "bos_token_id": 1, | |
| "context_length": 4096, | |
| "decoder": { | |
| "session_options": { | |
| "log_id": "onnxruntime-genai", | |
| "provider_options": [ | |
| { | |
| "cuda": { | |
| "enable_cuda_graph": "0", | |
| "enable_skip_layer_norm_strict_mode": "1" | |
| } | |
| } | |
| ] | |
| }, | |
| "filename": "model.onnx", | |
| "head_size": 64, | |
| "hidden_size": 768, | |
| "inputs": { | |
| "input_ids": "input_ids", | |
| "attention_mask": "attention_mask", | |
| "past_key_names": "past_key_values.%d.key", | |
| "past_value_names": "past_key_values.%d.value" | |
| }, | |
| "outputs": { | |
| "logits": "logits", | |
| "present_key_names": "present.%d.key", | |
| "present_value_names": "present.%d.value" | |
| }, | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 16, | |
| "num_key_value_heads": 4 | |
| }, | |
| "eos_token_id": [ | |
| 375 | |
| ], | |
| "pad_token_id": 375, | |
| "type": "qwen3", | |
| "vocab_size": 14202 | |
| }, | |
| "search": { | |
| "diversity_penalty": 0.0, | |
| "do_sample": false, | |
| "early_stopping": true, | |
| "length_penalty": 1.0, | |
| "max_length": 4096, | |
| "min_length": 0, | |
| "no_repeat_ngram_size": 0, | |
| "num_beams": 1, | |
| "num_return_sequences": 1, | |
| "past_present_share_buffer": true, | |
| "repetition_penalty": 1.0, | |
| "temperature": 1.0, | |
| "top_k": 50, | |
| "top_p": 1.0 | |
| } | |
| } |