Instructions to use jonatasgrosman/exp_w2v2t_th_vp-fr_s77 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/exp_w2v2t_th_vp-fr_s77 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/exp_w2v2t_th_vp-fr_s77")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/exp_w2v2t_th_vp-fr_s77") model = AutoModelForCTC.from_pretrained("jonatasgrosman/exp_w2v2t_th_vp-fr_s77", device_map="auto") - Notebooks
- Google Colab
- Kaggle
exp_w2v2t_th_vp-fr_s77
Fine-tuned facebook/wav2vec2-large-fr-voxpopuli for speech recognition on Thai 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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