Instructions to use kehanlu/mandarin-wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kehanlu/mandarin-wav2vec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="kehanlu/mandarin-wav2vec2")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("kehanlu/mandarin-wav2vec2") model = AutoModel.from_pretrained("kehanlu/mandarin-wav2vec2") - 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:c024abf35c970987105c9d4ed513de9a9f44e0f6c64f46fd5383c9faa2ab027b
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size 377510584
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