Instructions to use eugenetanjc/wav2vec_cv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eugenetanjc/wav2vec_cv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="eugenetanjc/wav2vec_cv")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("eugenetanjc/wav2vec_cv") model = AutoModelForCTC.from_pretrained("eugenetanjc/wav2vec_cv", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d1187a67613486382c6c298f8532a940ef7fb294e64b5277b09007b8a41140a7
- Size of remote file:
- 378 MB
- SHA256:
- e88f9d3807d044ceae26312867213a2b2149a0a7212b827de3a72e145824afb1
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