Instructions to use LBR47/whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use LBR47/whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="LBR47/whisper-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("LBR47/whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("LBR47/whisper-tiny", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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# whisper-tiny
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
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## Model description
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# whisper-tiny
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6624
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- Wer: 0.1833
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## Model description
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