Instructions to use jonatasgrosman/exp_w2v2t_zh-cn_unispeech-ml_s772 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jonatasgrosman/exp_w2v2t_zh-cn_unispeech-ml_s772 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="jonatasgrosman/exp_w2v2t_zh-cn_unispeech-ml_s772")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("jonatasgrosman/exp_w2v2t_zh-cn_unispeech-ml_s772") model = AutoModelForCTC.from_pretrained("jonatasgrosman/exp_w2v2t_zh-cn_unispeech-ml_s772", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 314 Bytes
86377f3 | 1 | {"unk_token": "<unk>", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "<pad>", "do_lower_case": false, "word_delimiter_token": "|", "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "/tmp/tmpmgn5lik7", "tokenizer_class": "Wav2Vec2CTCTokenizer", "processor_class": "Wav2Vec2Processor"} |