Instructions to use eengel7/train_first_try with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use eengel7/train_first_try with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="eengel7/train_first_try")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("eengel7/train_first_try") model = AutoModelForSpeechSeq2Seq.from_pretrained("eengel7/train_first_try", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 204118eecdb0fd5169578577ed28964665a17afb43d9674098352bc72dd9a138
- Size of remote file:
- 967 MB
- SHA256:
- b332ea66408bdf383c10e57c91c14a6799af192b1b5a67c0c38096f9b5b5582c
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