Instructions to use hf-tiny-model-private/tiny-random-HubertForCTC 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-HubertForCTC 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-HubertForCTC")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-HubertForCTC") model = AutoModelForCTC.from_pretrained("hf-tiny-model-private/tiny-random-HubertForCTC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b2d5dff4d2d17a0c6bf812c3e3f9f966748af50b978ed832ba4d6dc469ad93d2
- Size of remote file:
- 135 kB
- SHA256:
- 19b7708b81da3ac9c0b88c3805f5498343688f88668cbfa2008b4126c87457e3
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