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:
- f44c6c2051e9b5bc0f4529d7d33cb88f43a2691fc2db0da038c341f0112c32dd
- Size of remote file:
- 23.3 MB
- SHA256:
- ef4a9a73a6e7aa3a87ca61da5dae3e63f2801ec0a86604f26934c405535fc45e
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