Instructions to use alefiury/wav2vec2-large-xlsr-53-gender-recognition-librispeech with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use alefiury/wav2vec2-large-xlsr-53-gender-recognition-librispeech with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="alefiury/wav2vec2-large-xlsr-53-gender-recognition-librispeech")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("alefiury/wav2vec2-large-xlsr-53-gender-recognition-librispeech") model = AutoModelForAudioClassification.from_pretrained("alefiury/wav2vec2-large-xlsr-53-gender-recognition-librispeech", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
86366c6
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Parent(s): af06d54
Librarian Bot: Add base_model information to model (#6)
Browse files- Librarian Bot: Add base_model information to model (565842e9934ed31307e10ff97c1d1db8b10d253b)
Co-authored-by: Librarian Bot (Bot) <librarian-bot@users.noreply.huggingface.co>
README.md
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- f1
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model-index:
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- name: weights
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results: []
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datasets:
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- librispeech_asr
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- librispeech_asr
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metrics:
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- f1
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base_model: facebook/wav2vec2-xls-r-300m
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model-index:
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- name: weights
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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