Instructions to use jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459") model = AutoModelForCTC.from_pretrained("jonatasgrosman/exp_w2v2t_en_unispeech-sat_s459", device_map="auto") - Notebooks
- Google Colab
- Kaggle
exp_w2v2t_en_unispeech-sat_s459
Fine-tuned microsoft/unispeech-sat-large for speech recognition on English using the train split of Common Voice 7.0. When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned by the HuggingSound tool.
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