Model Details
Full Model IDtiantiaf/voxlect-mandarin-cantonese-dialect-mms-lid-256
Pipeline / Taskaudio-classification
Librarytransformers
Downloads (all-time)10
Likes1
Last Modified8/10/2025
Author / Orgtiantiaf
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="tiantiaf/voxlect-mandarin-cantonese-dialect-mms-lid-256")
# Run inference
result = pipe("Your input here")
print(result)🏷️ Tags
transformerssafetensorsmodel_hub_mixinpytorch_model_hub_mixinspeaker_dialect_classificationaudio-classificationzhdataset:mozilla-foundation/common_voice_11_0arxiv:2508.01691base_model:facebook/mms-lid-256base_model:finetune:facebook/mms-lid-256license:cc-by-nc-4.0endpoints_compatibleregion:us
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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
⬇ Downloads10
❤️ Community Likes1
🛠️ Requirements
- →Install: pip install transformers
- →Python 3.8+ recommended for Transformers.
- →GPU (CUDA) speeds up inference significantly.
- →Use model.half() for fp16 on limited VRAM.