Model Details
Full Model IDmudler/ced-gguf
Pipeline / Taskaudio-classification
Libraryced.cpp
Downloads (all-time)11.2K
Likes5
Last Modified6/21/2026
Author / Orgmudler
PrivateNo — public
⚡ Quick Usage (Python)
Using the 🤗 Transformers library. Install with pip install transformers
from transformers import pipeline
# Load the model
pipe = pipeline("audio-classification", model="mudler/ced-gguf")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
ced.cppggufaudio-classificationsound-event-detectionaudio-taggingaudiosetggmlcedbase_model:mispeech/ced-basebase_model:quantized:mispeech/ced-baselicense:apache-2.0region:us
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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: audio-classification
This model is designed for the audio-classification task. Explore more models for this use case.
All audio-classification Models →📊 Popularity
⬇ Downloads11.2K
❤️ Community Likes5
🛠️ Requirements
- →Install: pip install ced.cpp
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.