Feature Extraction
sentence-transformers
Safetensors
English
qwen2_5_omni_thinker
audio
speech
emotion
clap
contrastive
voice
Instructions to use VoiceNet/voiceclap-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use VoiceNet/voiceclap-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("VoiceNet/voiceclap-large") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2d27d1c78f86fec365dbe1e0f75b35dbcb52725f8168d553fd18283ff514ba99
- Size of remote file:
- 11.4 MB
- SHA256:
- 0c75e6d39795d574e5ec741e767ca690ea08a33bfa024ef2d372b4e4c72db191
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