Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Oriya
whisper
whisper-event
Generated from Trainer
oriya
Eval Results (legacy)
Instructions to use Ranjit/Whisper_Small_Odia_10k_steps with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ranjit/Whisper_Small_Odia_10k_steps with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Ranjit/Whisper_Small_Odia_10k_steps")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Ranjit/Whisper_Small_Odia_10k_steps") model = AutoModelForSpeechSeq2Seq.from_pretrained("Ranjit/Whisper_Small_Odia_10k_steps", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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### Framework versions
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- Transformers 4.28.0.dev0
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- Pytorch 1.11.0+cu113
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- Datasets 2.10.1
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- Tokenizers 0.13.2
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<!-- ### Framework versions
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