Instructions to use thejuuuuu/torgo_b2_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thejuuuuu/torgo_b2_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="thejuuuuu/torgo_b2_2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("thejuuuuu/torgo_b2_2") model = AutoModelForCTC.from_pretrained("thejuuuuu/torgo_b2_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9742601eb0c50c160560c71613a9572af683701b6de90a3f322bf990b5978552
- Size of remote file:
- 1.26 GB
- SHA256:
- cfa574366efd8d96643e8ff8207a1e88011b77ce7555c1a6fbdb67682539da2a
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