Instructions to use proseph/ctrlv-wav2vec2-tokenizer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use proseph/ctrlv-wav2vec2-tokenizer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="proseph/ctrlv-wav2vec2-tokenizer")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("proseph/ctrlv-wav2vec2-tokenizer") model = AutoModelForCTC.from_pretrained("proseph/ctrlv-wav2vec2-tokenizer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 181 Bytes
3a9ae0d | 1 | {"unk_token": "[UNK]", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "[PAD]", "do_lower_case": false, "word_delimiter_token": "|", "tokenizer_class": "Wav2Vec2CTCTokenizer"} |