Instructions to use hf-tiny-model-private/tiny-random-MCTCTForCTC 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-MCTCTForCTC 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-MCTCTForCTC")# Load model directly from transformers import AutoModelForCTC model = AutoModelForCTC.from_pretrained("hf-tiny-model-private/tiny-random-MCTCTForCTC", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b29e2995943275dfc7c6ae8a32be1224a41ed38c31168c1011e62358fcf4d54c
- Size of remote file:
- 23.3 MB
- SHA256:
- 577047b34475d8a3ac1b77db80e2110399b9290f673db3b4573b4da4e989ec84
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