Audio Classification
Transformers
PyTorch
wav2vec2
pretraining
music
audio
speech
audio-representation-learning
arch-benchmark
general-audio
Instructions to use ALM/wav2vec2-base-audioset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ALM/wav2vec2-base-audioset with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="ALM/wav2vec2-base-audioset")# Load model directly from transformers import AutoProcessor, AutoModelForPreTraining processor = AutoProcessor.from_pretrained("ALM/wav2vec2-base-audioset") model = AutoModelForPreTraining.from_pretrained("ALM/wav2vec2-base-audioset") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
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oid sha256:43a1640045e80b38c688a234ad84f51fd8b3a2c8b362cd0428370dc220ee548a
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size 380204696
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