Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Oriya
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use auro/whisper-cli-small-or with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use auro/whisper-cli-small-or with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="auro/whisper-cli-small-or")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("auro/whisper-cli-small-or") model = AutoModelForSpeechSeq2Seq.from_pretrained("auro/whisper-cli-small-or") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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oid sha256:e586fdeb29cfe573988ee9c1a4c8d173a10a105212833cab6a87d7d15c84947f
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size 966995080
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