Instructions to use hf-internal-testing/tiny-random-Data2VecAudioForCTC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Data2VecAudioForCTC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-internal-testing/tiny-random-Data2VecAudioForCTC")# Load model directly from transformers import AutoTokenizer, AutoModelForCTC tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-Data2VecAudioForCTC") model = AutoModelForCTC.from_pretrained("hf-internal-testing/tiny-random-Data2VecAudioForCTC") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c56974d6ffb66f5f5a67ebded59b9c7eaef0c561bd5ced62a232c68eec018cdb
- Size of remote file:
- 272 kB
- SHA256:
- c30f7208911b6ba6deecc146131c16688a55b2c9a2aa7163898ed9c84182821a
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