Model Details
Full Model IDxbgoose/hubert-large-speech-emotion-recognition-russian-dusha-finetuned
Pipeline / Taskaudio-classification
Librarytransformers
Downloads (all-time)324.1K
Likes15
Last Modified4/26/2024
Author / Orgxbgoose
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="xbgoose/hubert-large-speech-emotion-recognition-russian-dusha-finetuned")
# Run inference
result = pipe("Your input here")
print(result)����� Tags
transformerspytorchsafetensorshubertaudio-classificationSERspeechaudiorussianrudataset:xbgoose/dushabase_model:facebook/hubert-large-ls960-ftbase_model:finetune:facebook/hubert-large-ls960-ftlicense:apache-2.0endpoints_compatibledeploy:azureregion: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
⬇ Downloads324.1K
����� Community Likes15
🛠�� 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.