Audio Classification
Transformers
Safetensors
unispeech-sat
emotion-recognition
speech-emotion-recognition
speech
multilingual
russian
quantized
compressed-tensors
int8
fp8
int4
Eval Results (legacy)
Instructions to use Aniemore/unispeech-sat-emotion-v1-crosslingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aniemore/unispeech-sat-emotion-v1-crosslingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Aniemore/unispeech-sat-emotion-v1-crosslingual")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Aniemore/unispeech-sat-emotion-v1-crosslingual") model = AutoModelForAudioClassification.from_pretrained("Aniemore/unispeech-sat-emotion-v1-crosslingual", device_map="auto") - Notebooks
- Google Colab
- Kaggle