Instructions to use rav2040/wav2vec2-base-timit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rav2040/wav2vec2-base-timit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rav2040/wav2vec2-base-timit")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("rav2040/wav2vec2-base-timit") model = AutoModelForCTC.from_pretrained("rav2040/wav2vec2-base-timit") - Notebooks
- Google Colab
- Kaggle
Upload special_tokens_map.json
Browse files- special_tokens_map.json +6 -0
special_tokens_map.json
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{
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"bos_token": "<s>",
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"eos_token": "</s>",
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"pad_token": "[PAD]",
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"unk_token": "[UNK]"
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}
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