Automatic Speech Recognition
Transformers
Safetensors
Chinese
wav2vec2
ctc
phoneme-recognition
singing
alignment
lora
audio
Instructions to use lyonlu13/wav2vec2-large-zh-singing-phoneme-ctc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lyonlu13/wav2vec2-large-zh-singing-phoneme-ctc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lyonlu13/wav2vec2-large-zh-singing-phoneme-ctc")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("lyonlu13/wav2vec2-large-zh-singing-phoneme-ctc") model = AutoModelForCTC.from_pretrained("lyonlu13/wav2vec2-large-zh-singing-phoneme-ctc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from lyonlu13/wav2vec2-large-zh-singing-phoneme-ctc: direct link, hf CLI and curl.
- Browser
- Download file 299 Bytes
-
https://huggingface.co/lyonlu13/wav2vec2-large-zh-singing-phoneme-ctc/resolve/main/processor_config.json
- Command line
-
hf download hf://lyonlu13/wav2vec2-large-zh-singing-phoneme-ctc/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/lyonlu13/wav2vec2-large-zh-singing-phoneme-ctc/resolve/main/processor_config.json
299 Bytes
| { | |
| "feature_extractor": { | |
| "do_normalize": true, | |
| "feature_extractor_type": "Wav2Vec2FeatureExtractor", | |
| "feature_size": 1, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000 | |
| }, | |
| "processor_class": "Wav2Vec2Processor" | |
| } | |