Automatic Speech Recognition
Transformers
Safetensors
wavlm
audio
speech
ctc
phone-recognition
arpabet
Instructions to use huper29/huper_recognizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use huper29/huper_recognizer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="huper29/huper_recognizer")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("huper29/huper_recognizer") model = AutoModelForCTC.from_pretrained("huper29/huper_recognizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add library name, pipeline tag, and links to paper and code
Verified signatureThis PR adds the missing `library_name` and `pipeline_tag` metadata to the model card. This enables the automated `transformers` usage snippet and makes the model discoverable under the `automatic-speech-recognition` pipeline tag. It also links the model card to the paper page and to the GitHub repository.c10c853
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Update README.md (#1)
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