Instructions to use hf-internal-testing/tiny-random-wav2vec2-conformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-wav2vec2-conformer 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-wav2vec2-conformer")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-wav2vec2-conformer") model = AutoModelForCTC.from_pretrained("hf-internal-testing/tiny-random-wav2vec2-conformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5657e2fa5f4584265fd97b99ef3f92317168591c8bca165878de4b7440e592d4
- Size of remote file:
- 203 kB
- SHA256:
- c5f5ad2458fd5777fc5109cf2093a8f4013c98d98cf0c53d778a672be4664bc6
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