Audio Classification
Transformers
Safetensors
feature-extraction
emotion-recognition
speech-emotion-recognition
speech
multilingual
russian
quantized
compressed-tensors
int8
fp8
int4
custom_code
Eval Results (legacy)
Instructions to use Aniemore/wavlm-bert-base-s-emotion-v1-crosslingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Aniemore/wavlm-bert-base-s-emotion-v1-crosslingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Aniemore/wavlm-bert-base-s-emotion-v1-crosslingual", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Aniemore/wavlm-bert-base-s-emotion-v1-crosslingual", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
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