This model is not packaged as a standard transformers checkpoint. The recommended way to use it is through the project inference code from GitHub.

Quick Start

1. Clone the GitHub repository

bash

git clone https://github.com/thangquang09/vietnamese-f5tts-voice-design.git
cd vietnamese-f5tts-voice-design
pip install -r requirements.txt

2. Run the Python API

python

from api import InstructVoiceAPI

tts = InstructVoiceAPI(
    device="cuda:0",
    hf_model_repo="thangquang09/capspeech-nar-vietnamese-stage2",
)

tts.synthesize(
    text="Xin chào, rất vui được gặp bạn.",
    caption="Giọng nữ trẻ, nhẹ nhàng, vui vẻ",
    output_path="output.wav",
)

3. Run the Gradio app

bash

python app.py \
  --hf_model_repo thangquang09/capspeech-nar-vietnamese-stage2 \
  --device cuda:0 \
  --port 7860

Files In This Repository

checkpoint.pt: Stage 2 model weights
finetune_vn_stage2.yaml: training/inference config
vocab.txt: Vietnamese text vocabulary
duration_predictor/: duration prediction module
README.md: model card

Notes

This is a custom CapSpeech-based release, so users should rely on the GitHub inference code rather than generic Hugging Face auto-loading APIs.
If you build demos or benchmarks on top of this model, please make sure your prompt format matches the instruction style shown above.

How To Read Download Counts

Hugging Face exposes repository-level download statistics.

In the UI

Open:

https://huggingface.co/thangquang09/capspeech-nar-vietnamese-stage2

and look for:

Downloads last month

In Python

python

from huggingface_hub import HfApi

api = HfApi()
info = api.model_info(
    "thangquang09/capspeech-nar-vietnamese-stage2",
    expand=["downloads", "downloadsAllTime"],
)

print("Downloads last 30 days:", info.downloads)
print(
    "Downloads all time:",
    getattr(info, "downloads_all_time", None) or getattr(info, "downloadsAllTime", None),
)

Citation

If you use this model, please cite:

the original CapSpeech project: https://github.com/WangHelin1997/CapSpeech
this Vietnamese adaptation/release: https://github.com/thangquang09/vietnamese-f5tts-voice-design

Acknowledgements

This model is built on top of:

CapSpeech
BigVGAN
ViT5
the Vietnamese instruction-TTS data pipeline developed in this project

Experiment Override

This repo is cloned from thangquang09/capspeech-nar-vietnamese-stage2-v3 and overrides:

checkpoint.pt
vocab.txt
finetune_vn_stage2_v3.yaml / finetune_vn_stage2.yaml / finetune_vn.yaml

thangquang09/capspeech-nar-vietnamese-stage2-v3-syllable5k-exp1

CapSpeech NAR Vietnamese Stage 2

What This Model Does

Main Differences From Stage 1

Model Overview

Intended Use