Instructions to use JovialValley/model_broadclass_onSet0try1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JovialValley/model_broadclass_onSet0try1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="JovialValley/model_broadclass_onSet0try1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("JovialValley/model_broadclass_onSet0try1") model = AutoModelForCTC.from_pretrained("JovialValley/model_broadclass_onSet0try1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Upload Wav2Vec2ForCTC
16786d7 -
Upload tokenizer
6681e87 -
update model card README.md
a88ec5b -
End of training
fe8bf98 -
Training in progress, step 100
250454b -
initial commit
ff427e1