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
File size: 942 Bytes
f6fc423 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | {
"add_prefix_space": false,
"audio_bos_token": "<|audio_bos|>",
"audio_eos_token": "<|audio_eos|>",
"audio_token": "<|AUDIO|>",
"backend": "tokenizers",
"bos_token": null,
"clean_up_tokenization_spaces": false,
"eos_token": "<|im_end|>",
"errors": "replace",
"image_token": "<|IMAGE|>",
"is_local": true,
"model_max_length": 32768,
"model_specific_special_tokens": {
"audio_bos_token": "<|audio_bos|>",
"audio_eos_token": "<|audio_eos|>",
"audio_token": "<|AUDIO|>",
"image_token": "<|IMAGE|>",
"video_token": "<|VIDEO|>",
"vision_bos_token": "<|vision_bos|>",
"vision_eos_token": "<|vision_eos|>"
},
"pad_token": "<|endoftext|>",
"processor_class": "Qwen2_5OmniProcessor",
"split_special_tokens": false,
"tokenizer_class": "TokenizersBackend",
"unk_token": null,
"video_token": "<|VIDEO|>",
"vision_bos_token": "<|vision_bos|>",
"vision_eos_token": "<|vision_eos|>"
}
|