Instructions to use Wikidepia/w2v2-id-tmp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wikidepia/w2v2-id-tmp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Wikidepia/w2v2-id-tmp")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Wikidepia/w2v2-id-tmp") model = AutoModelForCTC.from_pretrained("Wikidepia/w2v2-id-tmp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 395e4057d67a4d334118e7a0f3bcc9ded613a3a65c4f4214031006af2a3b6415
- Size of remote file:
- 2.49 GB
- SHA256:
- 62921d931db0bbaa703a274abcf84bc7b9e42016aed5de44891ac95d815cb5f3
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