Feature Extraction
Transformers
Safetensors
voiceclap-small
audio
speech
emotion
clap
contrastive
voice
custom_code
Instructions to use laion/voiceclap-small-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use laion/voiceclap-small-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="laion/voiceclap-small-v2", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("laion/voiceclap-small-v2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from laion/voiceclap-small-v2: direct link, hf CLI and curl.
- Browser
- Download file 315 Bytes
-
https://huggingface.co/laion/voiceclap-small-v2/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://laion/voiceclap-small-v2/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/laion/voiceclap-small-v2/resolve/main/preprocessor_config.json
315 Bytes
| { | |
| "chunk_length": 30, | |
| "dither": 0.0, | |
| "feature_extractor_type": "WhisperFeatureExtractor", | |
| "feature_size": 80, | |
| "hop_length": 160, | |
| "n_fft": 400, | |
| "n_samples": 480000, | |
| "nb_max_frames": 3000, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "return_attention_mask": false, | |
| "sampling_rate": 16000 | |
| } | |