Automatic Speech Recognition
Transformers
Safetensors
prosody_to_text
feature-extraction
prosody
speech-recognition
custom_code
Instructions to use Daporte/prosody2text-weights with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Daporte/prosody2text-weights with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Daporte/prosody2text-weights", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Daporte/prosody2text-weights", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from Daporte/prosody2text-weights: direct link, hf CLI and curl.
- Browser
- Download file 570 Bytes
-
https://huggingface.co/Daporte/prosody2text-weights/resolve/main/config.json
- Command line
-
hf download hf://Daporte/prosody2text-weights/config.json
-
curl -L -o config.json https://huggingface.co/Daporte/prosody2text-weights/resolve/main/config.json
570 Bytes
| { | |
| "model_type": "prosody_to_text", | |
| "architectures": [ | |
| "ProsodyToTextModel" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_prosody.ProsodyToTextConfig", | |
| "AutoModel": "modeling_prosody.ProsodyToTextModel" | |
| }, | |
| "mel_bins": 12, | |
| "length_ratio": 0.5, | |
| "feature_rate_hz": 200.0, | |
| "f0_scale": 500.0, | |
| "intensity_scale": 100.0, | |
| "whisper_subfolder": "whisper", | |
| "tokenizer_subfolder": "tokenizer", | |
| "num_beams": 10, | |
| "language": "en", | |
| "no_repeat_ngram_size": 3, | |
| "max_new_tokens": 225, | |
| "conformer_subfolder": "conformer", | |
| "constrain": true | |
| } | |