Instructions to use Aratako/MioTTS-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Aratako/MioTTS-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Aratako/MioTTS-GGUF",
	filename="MioTTS-0.1B-BF16.gguf",
)

llm.create_chat_completion(
	messages = "\"The answer to the universe is 42\""
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Aratako/MioTTS-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Aratako/MioTTS-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Aratako/MioTTS-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf Aratako/MioTTS-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Aratako/MioTTS-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf Aratako/MioTTS-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Aratako/MioTTS-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf Aratako/MioTTS-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Aratako/MioTTS-GGUF:Q4_K_M

Use Docker

docker model run hf.co/Aratako/MioTTS-GGUF:Q4_K_M

LM Studio
Jan
Ollama
How to use Aratako/MioTTS-GGUF with Ollama:
```
ollama run hf.co/Aratako/MioTTS-GGUF:Q4_K_M
```

Unsloth Studio

How to use Aratako/MioTTS-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Aratako/MioTTS-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Aratako/MioTTS-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Aratako/MioTTS-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use Aratako/MioTTS-GGUF with Docker Model Runner:
```
docker model run hf.co/Aratako/MioTTS-GGUF:Q4_K_M
```

Lemonade

How to use Aratako/MioTTS-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Aratako/MioTTS-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.MioTTS-GGUF-Q4_K_M

List all available models

lemonade list

MioTTS-GGUF / README.md

Aratako

Create README.md

3192b3e verified 5 months ago

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	---
	pipeline_tag: text-to-speech
	tags:
	- speech
	- tts
	- voice
	- gguf
	license: other
	---

	# MioTTS-GGUF

	[![Hugging Face Collection](https://img.shields.io/badge/Collection-HuggingFace-yellow)](https://huggingface.co/collections/Aratako/miotts)
	[![Inference Code](https://img.shields.io/badge/Inference-GitHub-black)](https://github.com/Aratako/MioTTS-Inference)

	This repository contains GGUF quantized versions of the [MioTTS models](https://huggingface.co/collections/Aratako/miotts).
	MioTTS is a lightweight, high-speed Text-to-Speech (TTS) model family designed for high-quality English and Japanese speech generation.

	For model details, usage, and citations, please refer to the original model cards (linked below).

	## 📦 Available Models & Files

	\| Model Size \| Quantization \| File Name \| Size \| Original Model \|
	\| :--- \| :--- \| :--- \| :--- \| :--- \|
	\| 0.1B \| BF16 \| `MioTTS-0.1B-BF16.gguf` \| 232 MB \| [Link](https://huggingface.co/Aratako/MioTTS-0.1B) \|
	\| \| Q8_0 \| `MioTTS-0.1B-Q8_0.gguf` \| 125 MB \| \|
	\| \| Q6_K \| `MioTTS-0.1B-Q6_K.gguf` \| 97.3 MB \| \|
	\| \| Q4_K_M \| `MioTTS-0.1B-Q4_K_M.gguf` \| 79.6 MB \| \|
	\| 0.4B \| BF16 \| `MioTTS-0.4B-BF16.gguf` \| 736 MB \| [Link](https://huggingface.co/Aratako/MioTTS-0.4B) \|
	\| \| Q8_0 \| `MioTTS-0.4B-Q8_0.gguf` \| 392 MB \| \|
	\| \| Q6_K \| `MioTTS-0.4B-Q6_K.gguf` \| 304 MB \| \|
	\| \| Q4_K_M \| `MioTTS-0.4B-Q4_K_M.gguf` \| 239 MB \| \|
	\| 0.6B \| BF16 \| `MioTTS-0.6B-BF16.gguf` \| 1.22 GB \| [Link](https://huggingface.co/Aratako/MioTTS-0.6B) \|
	\| \| Q8_0 \| `MioTTS-0.6B-Q8_0.gguf` \| 653 MB \| \|
	\| \| Q6_K \| `MioTTS-0.6B-Q6_K.gguf` \| 506 MB \| \|
	\| \| Q4_K_M \| `MioTTS-0.6B-Q4_K_M.gguf` \| 408 MB \| \|
	\| 1.2B \| BF16 \| `MioTTS-1.2B-BF16.gguf` \| 2.39 GB \| [Link](https://huggingface.co/Aratako/MioTTS-1.2B) \|
	\| \| Q8_0 \| `MioTTS-1.2B-Q8_0.gguf` \| 1.27 GB \| \|
	\| \| Q6_K \| `MioTTS-1.2B-Q6_K.gguf` \| 983 MB \| \|
	\| \| Q4_K_M \| `MioTTS-1.2B-Q4_K_M.gguf` \| 751 MB \| \|
	\| 1.7B \| BF16 \| `MioTTS-1.7B-BF16.gguf` \| 3.5 GB \| [Link](https://huggingface.co/Aratako/MioTTS-1.7B) \|
	\| \| Q8_0 \| `MioTTS-1.7B-Q8_0.gguf` \| 1.86 GB \| \|
	\| \| Q6_K \| `MioTTS-1.7B-Q6_K.gguf` \| 1.44 GB \| \|
	\| \| Q4_K_M \| `MioTTS-1.7B-Q4_K_M.gguf` \| 1.13 GB \| \|
	\| 2.6B \| BF16 \| `MioTTS-2.6B-BF16.gguf` \| 5.19 GB \| [Link](https://huggingface.co/Aratako/MioTTS-2.6B) \|
	\| \| Q8_0 \| `MioTTS-2.6B-Q8_0.gguf` \| 2.76 GB \| \|
	\| \| Q6_K \| `MioTTS-2.6B-Q6_K.gguf` \| 2.13 GB \| \|
	\| \| Q4_K_M \| `MioTTS-2.6B-Q4_K_M.gguf` \| 1.58 GB \| \|

	## 🚀 Usage

	Please check the official inference repository for instructions on how to run these models.

	👉 [GitHub: Aratako/MioTTS-Inference](https://github.com/Aratako/MioTTS-Inference)

	## 📜 License

	Please note that the license differs depending on the model size (inherited from their respective base models). Please check the original model card for the specific license terms before use.

	* 0.1B: Falcon-LLM License
	* 0.4B, 1.2B, 2.6B: LFM Open License v1.0
	* 0.6B, 1.7B: Apache 2.0

	---
	pipeline_tag: text-to-speech
	tags:
	- speech
	- tts
	- voice
	- gguf
	license: other
	---

	# MioTTS-GGUF

	[![Hugging Face Collection](https://img.shields.io/badge/Collection-HuggingFace-yellow)](https://huggingface.co/collections/Aratako/miotts)
	[![Inference Code](https://img.shields.io/badge/Inference-GitHub-black)](https://github.com/Aratako/MioTTS-Inference)

	This repository contains GGUF quantized versions of the [MioTTS models](https://huggingface.co/collections/Aratako/miotts).
	MioTTS is a lightweight, high-speed Text-to-Speech (TTS) model family designed for high-quality English and Japanese speech generation.

	For model details, usage, and citations, please refer to the original model cards (linked below).

	## 📦 Available Models & Files

	\| Model Size \| Quantization \| File Name \| Size \| Original Model \|
	\| :--- \| :--- \| :--- \| :--- \| :--- \|
	\| 0.1B \| BF16 \| `MioTTS-0.1B-BF16.gguf` \| 232 MB \| [Link](https://huggingface.co/Aratako/MioTTS-0.1B) \|
	\| \| Q8_0 \| `MioTTS-0.1B-Q8_0.gguf` \| 125 MB \| \|
	\| \| Q6_K \| `MioTTS-0.1B-Q6_K.gguf` \| 97.3 MB \| \|
	\| \| Q4_K_M \| `MioTTS-0.1B-Q4_K_M.gguf` \| 79.6 MB \| \|
	\| 0.4B \| BF16 \| `MioTTS-0.4B-BF16.gguf` \| 736 MB \| [Link](https://huggingface.co/Aratako/MioTTS-0.4B) \|
	\| \| Q8_0 \| `MioTTS-0.4B-Q8_0.gguf` \| 392 MB \| \|
	\| \| Q6_K \| `MioTTS-0.4B-Q6_K.gguf` \| 304 MB \| \|
	\| \| Q4_K_M \| `MioTTS-0.4B-Q4_K_M.gguf` \| 239 MB \| \|
	\| 0.6B \| BF16 \| `MioTTS-0.6B-BF16.gguf` \| 1.22 GB \| [Link](https://huggingface.co/Aratako/MioTTS-0.6B) \|
	\| \| Q8_0 \| `MioTTS-0.6B-Q8_0.gguf` \| 653 MB \| \|
	\| \| Q6_K \| `MioTTS-0.6B-Q6_K.gguf` \| 506 MB \| \|
	\| \| Q4_K_M \| `MioTTS-0.6B-Q4_K_M.gguf` \| 408 MB \| \|
	\| 1.2B \| BF16 \| `MioTTS-1.2B-BF16.gguf` \| 2.39 GB \| [Link](https://huggingface.co/Aratako/MioTTS-1.2B) \|
	\| \| Q8_0 \| `MioTTS-1.2B-Q8_0.gguf` \| 1.27 GB \| \|
	\| \| Q6_K \| `MioTTS-1.2B-Q6_K.gguf` \| 983 MB \| \|
	\| \| Q4_K_M \| `MioTTS-1.2B-Q4_K_M.gguf` \| 751 MB \| \|
	\| 1.7B \| BF16 \| `MioTTS-1.7B-BF16.gguf` \| 3.5 GB \| [Link](https://huggingface.co/Aratako/MioTTS-1.7B) \|
	\| \| Q8_0 \| `MioTTS-1.7B-Q8_0.gguf` \| 1.86 GB \| \|
	\| \| Q6_K \| `MioTTS-1.7B-Q6_K.gguf` \| 1.44 GB \| \|
	\| \| Q4_K_M \| `MioTTS-1.7B-Q4_K_M.gguf` \| 1.13 GB \| \|
	\| 2.6B \| BF16 \| `MioTTS-2.6B-BF16.gguf` \| 5.19 GB \| [Link](https://huggingface.co/Aratako/MioTTS-2.6B) \|
	\| \| Q8_0 \| `MioTTS-2.6B-Q8_0.gguf` \| 2.76 GB \| \|
	\| \| Q6_K \| `MioTTS-2.6B-Q6_K.gguf` \| 2.13 GB \| \|
	\| \| Q4_K_M \| `MioTTS-2.6B-Q4_K_M.gguf` \| 1.58 GB \| \|

	## 🚀 Usage

	Please check the official inference repository for instructions on how to run these models.

	👉 [GitHub: Aratako/MioTTS-Inference](https://github.com/Aratako/MioTTS-Inference)

	## 📜 License

	Please note that the license differs depending on the model size (inherited from their respective base models). Please check the original model card for the specific license terms before use.

	* 0.1B: Falcon-LLM License
	* 0.4B, 1.2B, 2.6B: LFM Open License v1.0
	* 0.6B, 1.7B: Apache 2.0