Instructions to use Shubham09/wispher2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shubham09/wispher2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Shubham09/wispher2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Shubham09/wispher2") model = AutoModelForSpeechSeq2Seq.from_pretrained("Shubham09/wispher2") - Notebooks
- Google Colab
- Kaggle
Librarian Bot: Add base_model information to model
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README.md
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- generated_from_trainer
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metrics:
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- wer
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model-index:
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- name: wispher2
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results: []
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- generated_from_trainer
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metrics:
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base_model: openai/whisper-base.en
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model-index:
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- name: wispher2
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results: []
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