Audio Classification
Transformers
PyTorch
Safetensors
English
ser
wavlm
msp-podcast
emotion-recognition
audio
speech
valence
arousal
dominance
lucas
speech-emotion-recognition
custom_code
Instructions to use 3loi/SER-Odyssey-Baseline-WavLM-Multi-Attributes with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 3loi/SER-Odyssey-Baseline-WavLM-Multi-Attributes with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="3loi/SER-Odyssey-Baseline-WavLM-Multi-Attributes", trust_remote_code=True)# Load model directly from transformers import AutoModelForAudioClassification model = AutoModelForAudioClassification.from_pretrained("3loi/SER-Odyssey-Baseline-WavLM-Multi-Attributes", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by 3loi - opened
No description provided.
3loi changed pull request status to merged