Instructions to use aherzberg/ser_model_fixed_label with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aherzberg/ser_model_fixed_label with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="aherzberg/ser_model_fixed_label")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("aherzberg/ser_model_fixed_label") model = AutoModelForAudioClassification.from_pretrained("aherzberg/ser_model_fixed_label") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
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by librarian-bot - opened
README.md
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: ser_model_fixed_label
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results: []
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- generated_from_trainer
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metrics:
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- accuracy
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base_model: facebook/wav2vec2-base
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model-index:
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- name: ser_model_fixed_label
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results: []
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