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
| { | |
| "__version__": { | |
| "pytorch": "2.10.0+cu128", | |
| "sentence_transformers": "5.4.1", | |
| "transformers": "5.1.0" | |
| }, | |
| "default_prompt_name": "default", | |
| "model_type": "SentenceTransformer", | |
| "prompts": { | |
| "default": "You are Qwen, a virtual human developed by the Qwen Team, Alibaba Group, capable of perceiving auditory and visual inputs, as well as generating text and speech.", | |
| "document": "", | |
| "query": "" | |
| }, | |
| "similarity_fn_name": "cosine" | |
| } |