Instructions to use othrif/wav2vec_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use othrif/wav2vec_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="othrif/wav2vec_test")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("othrif/wav2vec_test") model = AutoModelForCTC.from_pretrained("othrif/wav2vec_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d676eea24773cfadbd197c41d7f9d7949d3b7dea0eaaeca34f0e01d2efde324
- Size of remote file:
- 2.29 kB
- SHA256:
- 4a949b13ad5afbc0f1621dd3c424c1db200517da21931d0b7976930beff9c6f6
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