Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use mouseyy/uk_wav2vec2_with_stress_mark with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mouseyy/uk_wav2vec2_with_stress_mark with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mouseyy/uk_wav2vec2_with_stress_mark")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("mouseyy/uk_wav2vec2_with_stress_mark") model = AutoModelForCTC.from_pretrained("mouseyy/uk_wav2vec2_with_stress_mark") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
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type: wer
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value: 0.2984287348943652
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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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- Transformers 4.49.0
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- Pytorch 2.6.0+cu124
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- Datasets 3.3.2
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- Tokenizers 0.21.0
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- name: Wer
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type: wer
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value: 0.2984287348943652
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language:
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- uk
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pipeline_tag: automatic-speech-recognition
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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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- Transformers 4.49.0
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- Pytorch 2.6.0+cu124
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- Datasets 3.3.2
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- Tokenizers 0.21.0
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