Instructions to use midoiv/result with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use midoiv/result with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="midoiv/result")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("midoiv/result") model = AutoModelForAudioClassification.from_pretrained("midoiv/result", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 3
Browse files
pytorch_model.bin
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runs/Apr03_20-19-54_5a3e4246b5e5/events.out.tfevents.1712175610.5a3e4246b5e5.17.0
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