Feature Extraction
sentence-transformers
Safetensors
Kernels
bidirectional_pplx_qwen3
multi-vector
custom_code
late-interaction
maxsim
pylate
text-embeddings-inference
Instructions to use perplexity-ai/pplx-embed-v1-late-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-late-0.6b with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("perplexity-ai/pplx-embed-v1-late-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] - Kernels
How to use perplexity-ai/pplx-embed-v1-late-0.6b with Kernels:
# !pip install kernels from kernels import get_kernel kernel = get_kernel("perplexity-ai/pplx-embed-v1-late-0.6b") - Notebooks
- Google Colab
- Kaggle
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