Feature Extraction
sentence-transformers
ONNX
Safetensors
multilingual
bidirectional_pplx_qwen3
sentence-similarity
mteb
custom_code
text-embeddings-inference
Instructions to use perplexity-ai/pplx-embed-v1-0.6b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use perplexity-ai/pplx-embed-v1-0.6b with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("perplexity-ai/pplx-embed-v1-0.6b", trust_remote_code=True) 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:
- c100a7572fbc4c692fede8b763f41ff49d04d932bdbfe3f1460236f8bed583b1
- Size of remote file:
- 1.03 MB
- SHA256:
- 63a6e460d1c0aab08674a944c2778403077c4ef27ccbe3a046057dfb4984d2ff
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