Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2-bert
Generated from Trainer
Instructions to use thiagolira/CiceroASR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thiagolira/CiceroASR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="thiagolira/CiceroASR")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("thiagolira/CiceroASR") model = AutoModelForCTC.from_pretrained("thiagolira/CiceroASR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0)
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for the transcription of Classical Latin!
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Example from the
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<video controls src="https://cdn-uploads.huggingface.co/production/uploads/5fc7944e8a82cc0bcf7cc51d/hYNFr2od1EKDlRRdzJmzR.webm"></video>
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Transcription:
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**arma virumque cano** (Of arms and men I sing)
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0)
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for the transcription of Classical Latin!
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Example from the Aeneid:
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<video controls src="https://cdn-uploads.huggingface.co/production/uploads/5fc7944e8a82cc0bcf7cc51d/hYNFr2od1EKDlRRdzJmzR.webm"></video>
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Transcription:
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**arma virumque cano** (Of arms and men I sing)
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