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
| from transformers.models.qwen3.configuration_qwen3 import Qwen3Config | |
| class PPLXQwen3Config(Qwen3Config): | |
| model_type = "bidirectional_pplx_qwen3" | |