Instructions to use aadel4/Wav2vec_Classroom_WSP_FT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aadel4/Wav2vec_Classroom_WSP_FT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="aadel4/Wav2vec_Classroom_WSP_FT")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("aadel4/Wav2vec_Classroom_WSP_FT") model = AutoModelForCTC.from_pretrained("aadel4/Wav2vec_Classroom_WSP_FT") - Notebooks
- Google Colab
- Kaggle
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README.md
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### Usage Request
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If you use the NCTE-WSP-ASR model in your research, please acknowledge this work and refer to the original paper submitted to Interspeech 2025.
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For inquiries or collaborations,
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### Usage Request
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If you use the NCTE-WSP-ASR model in your research, please acknowledge this work and refer to the original paper submitted to Interspeech 2025.
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For inquiries or collaborations, don't hesitate to contact me at aadel@umd.edu or ahmadadelattia@gmail.com
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