🤖 text-to-speech

AuK-Base-and-Flash-GGUF

audio-cpp/AuK-Base-and-Flash-GGUF

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Model Details
Full Model IDaudio-cpp/AuK-Base-and-Flash-GGUF
Pipeline / Tasktext-to-speech
Library—
Downloads (all-time)242.5K
Likes7
Last Modified9/21/2026
Author / Orgaudio-cpp
PrivateNo — public
⚡ Quick Usage (Python)

Using the 🤗 Transformers library. Install with pip install transformers

from transformers import pipeline

# Load the model
pipe = pipeline("text-to-speech", model="audio-cpp/AuK-Base-and-Flash-GGUF")

# Run inference
result = pipe("Your input here")
print(result)
🏷️ Tags
ggufaudiospeechtext-to-speechzero-shot-ttsvoice-cloningspeech-generationspeech-editingspeech-enhancementsource-separationspeech-separationinstruction-guideddiffusionaudio.cppbase_model:tencent/AuKbase_model:quantized:tencent/AuKlicense:mitregion:us
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🚀 Use This Model

Access model files, inference API, and full documentation on Hugging Face.

Open on Hugging Face →Browse Model Files ↗← Browse All Models
🤖 Task: text-to-speech

This model is designed for the text-to-speech task. Explore more models for this use case.

All text-to-speech Models →
📊 Popularity
⬇ Downloads242.5K
❤️ Community Likes7
🛠️ Requirements
  • →Check docs for installation steps.
  • →Python 3.8+ recommended for Transformers.
  • →GPU (CUDA) speeds up inference significantly.
  • →Use model.half() for fp16 on limited VRAM.
👋 Need help with code?