Instructions to use ThomasFG/67.5-67.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThomasFG/67.5-67.5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ThomasFG/67.5-67.5")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ThomasFG/67.5-67.5") model = AutoModelForSpeechSeq2Seq.from_pretrained("ThomasFG/67.5-67.5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ed4ec388537cf7d64b5a6aaa1b1cc2a3d0309e881abd3062ba11360766bb7045
- Size of remote file:
- 4.73 kB
- SHA256:
- d8bda8d42bb5c6a4d1dc29dc0661f705340f7abc5d4cc07a93ad12a645b75595
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