Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use sjhuskey/enenlhet-whisper-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sjhuskey/enenlhet-whisper-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sjhuskey/enenlhet-whisper-model")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("sjhuskey/enenlhet-whisper-model") model = AutoModelForSpeechSeq2Seq.from_pretrained("sjhuskey/enenlhet-whisper-model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 743b7feb5a1b3c8c754ec87d67ccd6af4066e8fe33ffb85d1f1fa71d1e7fb065
- Size of remote file:
- 5.97 kB
- SHA256:
- 8945c89a345fb3b27da9b5f162e48ddd77e86169e87c6198a3a40fec3a86531a
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