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
Download pytorch_model.bin from Aniemore/unispeech-sat-emotion-russian-resd: direct link, hf CLI and curl.
- Browser
- Download file 1.27 GB
-
https://huggingface.co/Aniemore/unispeech-sat-emotion-russian-resd/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Aniemore/unispeech-sat-emotion-russian-resd/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Aniemore/unispeech-sat-emotion-russian-resd/resolve/main/pytorch_model.bin
1.27 GB
- Xet hash:
- c13eb419e114545fc74f74529aacbbd5a87914997ef2ece60f38176ca265ab88
- Size of remote file:
- 1.27 GB
- SHA256:
- 275190b27abdb699df97212afea59bba1ce52c5e7b5c0d5e59156e7a52101c2e
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