Instructions to use ABBNDZ/ATTS1HG1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ABBNDZ/ATTS1HG1 with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="ABBNDZ/ATTS1HG1",
	filename="ATTS1HG1_FP16.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use ABBNDZ/ATTS1HG1 with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ABBNDZ/ATTS1HG1:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf ABBNDZ/ATTS1HG1:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ABBNDZ/ATTS1HG1:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf ABBNDZ/ATTS1HG1: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 ABBNDZ/ATTS1HG1:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf ABBNDZ/ATTS1HG1: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 ABBNDZ/ATTS1HG1:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ABBNDZ/ATTS1HG1:Q4_K_M

Use Docker

docker model run hf.co/ABBNDZ/ATTS1HG1:Q4_K_M

LM Studio
Jan
Ollama
How to use ABBNDZ/ATTS1HG1 with Ollama:
```
ollama run hf.co/ABBNDZ/ATTS1HG1:Q4_K_M
```

Unsloth Studio new

How to use ABBNDZ/ATTS1HG1 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 ABBNDZ/ATTS1HG1 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 ABBNDZ/ATTS1HG1 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ABBNDZ/ATTS1HG1 to start chatting

Docker Model Runner
How to use ABBNDZ/ATTS1HG1 with Docker Model Runner:
```
docker model run hf.co/ABBNDZ/ATTS1HG1:Q4_K_M
```

Lemonade

How to use ABBNDZ/ATTS1HG1 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ABBNDZ/ATTS1HG1:Q4_K_M

Run and chat with the model

lemonade run user.ATTS1HG1-Q4_K_M

List all available models

lemonade list

ATTS1HG1: High-Performance llama.cpp Implementation of XTTS-v2

ATTS1HG1 v1.1 is a high-speed, native C++ implementation of the Coqui XTTS-v2 model, utilizing the llama.cpp library. It features a custom integrated HiFiGAN vocoder optimized for Vulkan and CPU inference.

Source Code & GUI	Base Model	Backend
GitHub: ATTS1HG1	Coqui XTTS-v2	GGML / Vulkan

🚀 Key Features

Blazing Fast: Generates audio in < 0.5s on consumer GPUs (RTX 3090) and ~1.0s on CPU.
Vulkan Support: Fully optimized HiFiGAN vocoder running on Vulkan (compatible with NVIDIA, AMD, Intel iGPUs).
Lightweight: Native C++ application utilizing the llama.cpp, no heavy Python dependencies.
Multi-Language: Supports 17 languages.
Voice : Supports 58 speaker (similar to XTTS).

🌍 Supported Languages

The model supports the following 17 languages:

Code	Language	Native Name
en	English	English
es	Spanish	Español
fr	French	Français
de	German	Deutsch
it	Italian	Italiano
pt	Portuguese	Português
pl	Polish	Polski
tr	Turkish	Türkçe
ru	Russian	Русский
nl	Dutch	Nederlands
cs	Czech	Čeština
ar	Arabic	العربية
zh	Chinese	中文
ja	Japanese	日本語
hu	Hungarian	Magyar
ko	Korean	한국어
hi	Hindi	हिन्दी

⚡ Performance

Benchmarks based on standard text generation ("Bonjour le monde") using the C++ client:

Device	Backend	Latency (Total)	Note
NVIDIA RTX 3090	Vulkan	~0.47s	🚀 Recommended
Intel iGPU	Vulkan	~1.40s	Good for laptops
CPU (Ryzen/Intel)	CPU (AVX2)	~1.02s	Solid fallback
NVIDIA RTX 3090	CUDA	~1.45s	Slower on HiFiGAN due to kernel overhead

Note: The Vulkan backend is significantly faster for the HiFiGAN part of the pipeline compared to CUDA due to optimized command buffers and reduced kernel launch overhead for small convolutions.

🔧 Key Technical Upgrades

Split Model Architecture (GPT2 + HiFiGAN):
The text-to-latent model (GPT2) and the vocoder (HiFiGAN) are now separate GGUF files.
Allows users to load HiFiGAN via Vulkan for lower latency while keeping GPT2 optimized for CUDA.
Result: Up to 3x faster audio generation on RTX series.
Advanced Text Preprocessing:
Automatic Language Detection (New!):

ATTS now features a robust LanguageDetector class that analyzes input text. Uses Script Range (Unicode blocks), Dictionary (common words), and N-Grams (suffixes/patterns). Supports 17 languages with confidence scoring and fallback logic. In "Auto Mode" (LangDirIndex == 0), the system automatically selects the language for synthesis.
MeCab Integration: Native Japanese tokenization and segmentation for natural prosody.
Romanization: Automatic romanization for Chinese (Pinyin), Japanese (Romaji), and Korean (Revised Romanization).
Num2Words: Converts numbers (e.g., "123") into words ("one hundred twenty-three") across all 17

🛠️ Usage

This repository contains the converted .zip and .gguf weights required by the ATTS1HG1 software.

Zero-Configuration Deployment:

Download the Pre-compiled GUI Applications (.zip) and the model files from this repository.
No C++ compilation, no Python dependencies, no pip install.
Just unzip and run atts_gui_app_v1.1.exe.
Load the model in the GUI or CLI and select Vulkan for best performance.

🧠 Model Files (GGUF via llama.cpp)

atts1hg1_q6_k.gguf (Legacy: Combined GPT2+HiFiGAN)
ATTS1_q6_k.gguf (New: GPT2 Only)
hifigan1_FP16.gguf (New: HiFiGAN Only)

🔊 Sample Audio Files

Test the quality with these pre-generated samples covering various speakers and languages.

Filename	Speaker	Language	Download
Vjollca Johnnie	Vjollca Johnnie	French	⬇️ Download
Gitta Nikolina	Gitta Nikolina	Arabic	⬇️ Download
Damien Black	Damien Black	Chinese	⬇️ Download
Asya Anara	Asya Anara	English	⬇️ Download
Vjollca Johnnie	Vjollca Johnnie	Spanish	⬇️ Download
Nova Hogarth	Nova Hogarth	Hindi	⬇️ Download
Adde Michal	Adde Michal	Dutch	⬇️ Download
Craig Gutsy	Craig Gutsy	Czech	⬇️ Download
Dionisio Schuyler	Dionisio Schuyler	German	⬇️ Download
Dionisio Schuyler	Dionisio Schuyler	Italian	⬇️ Download
Ludvig Milivoj	Ludvig Milivoj	Hungarian	⬇️ Download
Royston Min	Royston Min	Portuguese	⬇️ Download
Viktor Eka	Viktor Eka	Polish	⬇️ Download
Abrahan Mack	Abrahan Mack	Russian	⬇️ Download
Abrahan Mack	Abrahan Mack	Turkish	⬇️ Download
Viktor Menelaos	Viktor Menelaos	Korean	⬇️ Download
Zacharie Aimilios	Zacharie Aimilios	Japanese	⬇️ Download