Instructions to use anton-l/wav2vec2-random-tiny-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anton-l/wav2vec2-random-tiny-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anton-l/wav2vec2-random-tiny-classifier")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anton-l/wav2vec2-random-tiny-classifier") model = AutoModelForAudioClassification.from_pretrained("anton-l/wav2vec2-random-tiny-classifier") - Notebooks
- Google Colab
- Kaggle
# Load model directly
from transformers import AutoProcessor, AutoModelForAudioClassification
processor = AutoProcessor.from_pretrained("anton-l/wav2vec2-random-tiny-classifier")
model = AutoModelForAudioClassification.from_pretrained("anton-l/wav2vec2-random-tiny-classifier")Quick Links
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# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anton-l/wav2vec2-random-tiny-classifier")