Instructions to use micsell/wav2vec2-base2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use micsell/wav2vec2-base2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="micsell/wav2vec2-base2")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("micsell/wav2vec2-base2") model = AutoModelForAudioClassification.from_pretrained("micsell/wav2vec2-base2", device_map="auto") - 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 sha256:1adfba2d40447ead83b84d3b3c9ea760670f2712a7a7bb63ca2aaa6e84386718
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size 378302360
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