Audio Classification
Transformers
PyTorch
Safetensors
Russian
unispeech-sat
emotion-recognition
speech-emotion-recognition
audio
speech
russian
Eval Results (legacy)
Instructions to use Aniemore/unispeech-sat-emotion-russian-resd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aniemore/unispeech-sat-emotion-russian-resd with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Aniemore/unispeech-sat-emotion-russian-resd")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Aniemore/unispeech-sat-emotion-russian-resd") model = AutoModelForAudioClassification.from_pretrained("Aniemore/unispeech-sat-emotion-russian-resd", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
2d35506
1
Parent(s): 9046f4e
Adding `safetensors` variant of this model (#2)
Browse files- Adding `safetensors` variant of this model (81e8fbe05f59d5b989ba68aafef92b50205d7b6b)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
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