Instructions to use abdouaziiz/wav2vec2-xls-r-300m-wolof-lm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abdouaziiz/wav2vec2-xls-r-300m-wolof-lm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="abdouaziiz/wav2vec2-xls-r-300m-wolof-lm")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("abdouaziiz/wav2vec2-xls-r-300m-wolof-lm") model = AutoModelForCTC.from_pretrained("abdouaziiz/wav2vec2-xls-r-300m-wolof-lm", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 454 Bytes
1c5b1a1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"bos_token": null,
"do_lower_case": false,
"eos_token": null,
"name_or_path": "abdouaziiz/wav2vec2-xls-r-300m-wolof",
"pad_token": "[PAD]",
"processor_class": "Wav2Vec2ProcessorWithLM",
"replace_word_delimiter_char": " ",
"special_tokens_map_file": "/WOLOF/wav2vec2-xls-r-300m-wolof/special_tokens_map.json",
"tokenizer_class": "Wav2Vec2CTCTokenizer",
"tokenizer_file": null,
"unk_token": "[UNK]",
"word_delimiter_token": "|"
}
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