Instructions to use hf-tiny-model-private/tiny-random-WavLMForCTC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-WavLMForCTC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-tiny-model-private/tiny-random-WavLMForCTC")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-WavLMForCTC") model = AutoModelForCTC.from_pretrained("hf-tiny-model-private/tiny-random-WavLMForCTC") - 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 sha256:13037edb05c5f1010f61c06311b4adc87c4b547acc2c7aeef46bd1ddef2527ed
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size 123136
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