Instructions to use jonatasgrosman/exp_w2v2t_sv-se_wavlm_s607 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/exp_w2v2t_sv-se_wavlm_s607 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/exp_w2v2t_sv-se_wavlm_s607")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/exp_w2v2t_sv-se_wavlm_s607") model = AutoModelForCTC.from_pretrained("jonatasgrosman/exp_w2v2t_sv-se_wavlm_s607") - Notebooks
- Google Colab
- Kaggle
YAML Metadata Error:"language[0]" must only contain lowercase characters
YAML Metadata Error:"language[0]" with value "sv-SE" is not valid. It must be an ISO 639-1, 639-2 or 639-3 code (two/three letters), or a special value like "code", "multilingual". If you want to use BCP-47 identifiers, you can specify them in language_bcp47.
exp_w2v2t_sv-se_wavlm_s607
Fine-tuned microsoft/wavlm-large for speech recognition using the train split of Common Voice 7.0 (sv-SE). 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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