OuteTTS-0.2-500M-GGUF Open-Source Multilingual Text-to-Speech Model - Supports English, Chinese, Japanese, and Korean Speech Synthesis

Outetts 0.2 500M GGUF

Developed by second-state

OuteTTS-0.2-500M is a multilingual text-to-speech model supporting English, Chinese, Japanese, and Korean.

Speech Synthesis Supports Multiple Languages#Multilingual TTS #Lightweight Speech Synthesis #Low-resource Deployment

Downloads 693

Release Time : 12/24/2024

Model Overview

This model is a 500M-parameter text-to-speech (TTS) model capable of converting input text into natural speech output, supporting multiple languages.

Model Features

Multilingual Support

Supports text-to-speech in four languages: English, Chinese, Japanese, and Korean.

Quantized Models

Provides multiple quantized versions of the model to accommodate different hardware and performance needs.

Efficient Inference

Optimized through GGUF format for efficient operation on various hardware platforms.

Model Capabilities

Text-to-Speech

Multilingual Speech Synthesis

Use Cases

Speech Synthesis

Voice Assistants

Provides natural speech output for voice assistants.

Audiobooks

Converts text content into speech for creating audiobooks.

🚀 OuteTTS-0.2-500M-GGUF

This project provides a quantized version of the OuteTTS-0.2-500M model, enabling efficient text-to-speech conversion. It supports multiple languages and can be easily integrated into the LlamaEdge service.

📦 Model Information

Property	Details
Base Model	OuteAI/OuteTTS-0.2-500M
Model Creator	OuteAI
Model Name	OuteTTS-0.2-500M
Quantized By	Second State Inc.
License	cc-by-nc-4.0
Languages	English, Chinese, Japanese, Korean
Pipeline Tag	text-to-speech

🚀 Quick Start

Run with LlamaEdge

LlamaEdge version: v0.14.9

Run as LlamaEdge service

wasmedge --dir .:. \
  --nn-preload tts:GGML:AUTO:OuteTTS-0.2-500M-Q5_K_M.gguf \
  llama-api-server.wasm config \
  --file llama_server_config.toml \
  --tts

llama_server_config.toml can be derived from the template config file llama_server_config.toml.bkp. The recommended [tts] config is shown as below:

[tts]
model_name   = "tts"            # Name of the TTS model.
model_alias  = "tts"            # Alias of the TTS model.
codec_model  = ""               # Required. Path to the codec model file.
speaker_file  = ""              # Path to an alternative speaker file.
ctx_size     = 8192             # Context size. Default is 8192.
batch_size   = 8192             # Batch size. Default is 8192.
ubatch_size  = 8192             # Physical maximum batch size. Default is 8192.
n_predict    = 4096             # Number of tokens to predict. Default is 4096.
n_gpu_layers = 100              # Number of layers to run on GPU. Default is 100.
temp         = 0.8              # Temperature. Default is 0.8.

💻 Quantized GGUF Models

Name	Quant method	Bits	Size	Use case
OuteTTS-0.2-500M-Q2_K.gguf	Q2_K	2	344 MB	smallest, significant quality loss - not recommended for most purposes
OuteTTS-0.2-500M-Q3_K_L.gguf	Q3_K_L	3	375 MB	small, substantial quality loss
OuteTTS-0.2-500M-Q3_K_M.gguf	Q3_K_M	3	361 MB	very small, high quality loss
OuteTTS-0.2-500M-Q3_K_S.gguf	Q3_K_S	3	344 MB	very small, high quality loss
OuteTTS-0.2-500M-Q4_0.gguf	Q4_0	4	358 MB	legacy; small, very high quality loss - prefer using Q3_K_M
OuteTTS-0.2-500M-Q4_K_M.gguf	Q4_K_M	4	403 MB	medium, balanced quality - recommended
OuteTTS-0.2-500M-Q4_K_S.gguf	Q4_K_S	4	391 MB	small, greater quality loss
OuteTTS-0.2-500M-Q5_0.gguf	Q5_0	5	402 MB	legacy; medium, balanced quality - prefer using Q4_K_M
OuteTTS-0.2-500M-Q5_K_M.gguf	Q5_K_M	5	426 MB	large, very low quality loss - recommended
OuteTTS-0.2-500M-Q5_K_S.gguf	Q5_K_S	5	418 MB	large, low quality loss - recommended
OuteTTS-0.2-500M-Q6_K.gguf	Q6_K	6	511 MB	very large, extremely low quality loss
OuteTTS-0.2-500M-Q8_0.gguf	Q8_0	8	537 MB	very large, extremely low quality loss - not recommended
OuteTTS-0.2-500M-f16.gguf	f16	16	1.00 GB
wavtokenizer-large-75-ggml-f16.gguf	f16	16	1.00 GB

Quantized with llama.cpp b4381

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