Instructions to use hf-internal-testing/processor_with_lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/processor_with_lm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-internal-testing/processor_with_lm")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hf-internal-testing/processor_with_lm") model = AutoModelForCTC.from_pretrained("hf-internal-testing/processor_with_lm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b492e631da1661c3375b387d10269e90ad7748aa841fe55c3c85991288a57532
- Size of remote file:
- 140 kB
- SHA256:
- 3423d4b48d52919581eb5e711a77b8e358ee3700181be150fb3f6a6c227d35a4
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