Model Details
Full Model IDJmica/Drama-3-GGUF
Pipeline / Tasktext-to-speech
Library—
Downloads (all-time)269.5K
Likes30
Last Modified10/16/2026
Author / OrgJmica
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="Jmica/Drama-3-GGUF")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
ggufaudio.cppfish-audiotext-to-speechvoice-cloningaudio-editingmoemixed-quantizationbase_model:fishaudio/drama-3base_model:quantized:fishaudio/drama-3license:otherregion:us
More text-to-speech Models
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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
⬇ Downloads269.5K
❤️ Community Likes30
🛠️ 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.