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") - Notebooks
- Google Colab
- Kaggle
Merge branch 'main' of https://huggingface.co/hf-internal-testing/processor_with_lm into main
Browse files- preprocessor_config.json +1 -1
preprocessor_config.json
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{"feature_size": 1, "padding_value": 0.0, "sampling_rate": 16000, "return_attention_mask": false, "do_normalize": true}
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{"feature_size": 1, "padding_value": 0.0, "sampling_rate": 16000, "return_attention_mask": false, "do_normalize": true, "processor_class": "Wav2Vec2ProcessorWithLM"}
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