Instructions to use TheAIchemist13/kannada_beekeeping_wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheAIchemist13/kannada_beekeeping_wav2vec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="TheAIchemist13/kannada_beekeeping_wav2vec2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("TheAIchemist13/kannada_beekeeping_wav2vec2") model = AutoModelForCTC.from_pretrained("TheAIchemist13/kannada_beekeeping_wav2vec2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2464422b786b3edf7f8d0e12507e8d672983792130ee62577921002f0b56bac5
- Size of remote file:
- 378 MB
- SHA256:
- 60dd25c59c1c27bb9cd6bc7a625105d3001fde117d3e92fa8cbd19a67767e0a6
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