Model Details
Full Model IDaufklarer/Qwen3-ForcedAligner-0.6B-4bit
Pipeline / Taskaudio-classification
Librarymlx
Downloads (all-time)33.3K
Likes1
Last Modified4/12/2026
Author / Orgaufklarer
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="aufklarer/Qwen3-ForcedAligner-0.6B-4bit")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
mlxsafetensorsqwen3_asrforced-alignmentspeechqwen3audiotimestamps4bitquantizedaudio-classificationenzhjakodefresitrubase_model:Qwen/Qwen3-ForcedAligner-0.6Bbase_model:finetune:Qwen/Qwen3-ForcedAligner-0.6Blicense:apache-2.0region:us
More audio-classification 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: audio-classification
This model is designed for the audio-classification task. Explore more models for this use case.
All audio-classification Models →📊 Popularity
⬇ Downloads33.3K
❤️ Community Likes1
🛠️ Requirements
- →Install: pip install mlx
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.