Any-to-Any
Transformers
ONNX
Safetensors
multilingual
qwen2
omni
custom_code
audio
speech
voice cloning
live Streaming
realtime speech conversation
asr
tts
text-generation-inference
Instructions to use jdh-algo/JoyTTS-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jdh-algo/JoyTTS-v1 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("jdh-algo/JoyTTS-v1", trust_remote_code=True) model = AutoModel.from_pretrained("jdh-algo/JoyTTS-v1", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
pipeline_tag: any-to-any
license: mit
library_name: transformers
language:
- multilingual
tags:
- omni
- custom_code
- audio
- speech
- voice cloning
- live Streaming
- realtime speech conversation
- asr
- tts
JoyTTS: LLM-based Spoken Chatbot With Voice Cloning
๐ Introduction
JoyTTS is an end-to-end spoken chatbot that combines large language models (LLM) with text-to-speech (TTS) technology, featuring voice cloning capabilities. This project is built upon the open-source MiniCPM-o and CosyVoice2 models and trained on 2000 hours of conversational data. We have also provided the complete training code to facilitate further development and optimization by the community. On the testing machine seed-tts-zh, it achieves a SM (Similarity Measure) score of 73 and a WER (Word Error Rate) of 5.