Instructions to use kehanlu/mandarin-wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kehanlu/mandarin-wav2vec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="kehanlu/mandarin-wav2vec2")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("kehanlu/mandarin-wav2vec2") model = AutoModel.from_pretrained("kehanlu/mandarin-wav2vec2") - Notebooks
- Google Colab
- Kaggle
| {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "<blank>", "do_lower_case": false, "word_delimiter_token": "|", "replace_word_delimiter_char": " ", "tokenizer_class": "Wav2Vec2CTCTokenizer", "processor_class": "Wav2Vec2Processor"} |