Instructions to use ABBNDZ/ATTS1HG1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
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
Update README.md
Browse files
README.md
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> **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.
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* Split Model Architecture (GPT2 + HiFiGAN):
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* Advanced Text Preprocessing:
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* **MeCab** Integration: Native Japanese tokenization and segmentation for natural prosody.
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* Romanization: Automatic romanization for Chinese (Pinyin), Japanese (Romaji), and Korean (Revised Romanization).
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* Num2Words: Converts numbers (e.g., "123") into words ("one hundred twenty-three") across all 17
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## 🛠️ Usage
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This repository contains the converted `.zip` and `.gguf` weights required by the ATTS1HG1 software.
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## 📜 License
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This project uses the weights from **Coqui XTTS-v2**, which is licensed under the **Coqui Public Model License (CPML)**.
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* **Non-commercial use:** You can use this model for personal, educational, and non-commercial projects.
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* **Commercial use:** Requires a license from Coqui (check their repository for details).
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The C++ code (inference engine) is available under the MIT License (see GitHub).
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*Credits: Based on the excellent work by Coqui.ai and the GGML library by ggerganov.*
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> **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.
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## 🔧 Key Technical Upgrades
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* Split Model Architecture (GPT2 + HiFiGAN):
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* Advanced Text Preprocessing:
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* Automatic Language Detection (New!):
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ATTS now features a robust LanguageDetector class that analyzes input text.
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Uses Script Range (Unicode blocks), Dictionary (common words), and N-Grams (suffixes/patterns).
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Supports 17 languages with confidence scoring and fallback logic.
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In "Auto Mode" (LangDirIndex == 0), the system automatically selects the language for synthesis.
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* **MeCab** Integration: Native Japanese tokenization and segmentation for natural prosody.
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* Romanization: Automatic romanization for Chinese (Pinyin), Japanese (Romaji), and Korean (Revised Romanization).
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* Num2Words: Converts numbers (e.g., "123") into words ("one hundred twenty-three") across all 17
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## 🛠️ Usage
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This repository contains the converted `.zip` and `.gguf` weights required by the ATTS1HG1 software.
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## 📜 License
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This project uses the weights from **Coqui XTTS-v2**, which is licensed under the **Coqui Public Model License (CPML)**.
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---
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*Credits: Based on the excellent work by Coqui.ai and the GGML library by ggerganov.*
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