Instructions to use jacktol/whisper-large-v3-finetuned-for-ATC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jacktol/whisper-large-v3-finetuned-for-ATC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jacktol/whisper-large-v3-finetuned-for-ATC")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("jacktol/whisper-large-v3-finetuned-for-ATC") model = AutoModelForMultimodalLM.from_pretrained("jacktol/whisper-large-v3-finetuned-for-ATC") - Notebooks
- Google Colab
- Kaggle
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README.md
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base_model:
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- openai/whisper-large-v3
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pipeline_tag: automatic-speech-recognition
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---
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base_model:
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- openai/whisper-large-v3
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pipeline_tag: automatic-speech-recognition
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model-index:
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- name: Whisper Large V3 Fine-Tuned for Air Traffic Control (ATC)
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results:
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- task:
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type: automatic-speech-recognition
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dataset:
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name: ATC ASR Dataset
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type: jacktol/ATC-ASR-Dataset
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metrics:
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- name: Word Error Rate (WER)
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type: wer
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value: 6.5
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---
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