Instructions to use cloudwalkerw/wavlm-base_2_predict with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cloudwalkerw/wavlm-base_2_predict with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="cloudwalkerw/wavlm-base_2_predict")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("cloudwalkerw/wavlm-base_2_predict") model = AutoModelForAudioClassification.from_pretrained("cloudwalkerw/wavlm-base_2_predict") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:001e49e1d939ecaefe694dbaf8635847e0cb3aeac25cac367940e93276f2ba38
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size 378347208
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