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-v1-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use perplexity-ai/pplx-embed-v1-4b with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("perplexity-ai/pplx-embed-v1-4b", 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
feat: config flag to support text-embeddings-inference
#3
by mkrimmel-pplx - opened
- config.json +2 -1
config.json
CHANGED
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@@ -72,5 +72,6 @@
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| 72 |
"use_cache": false,
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| 73 |
"use_sliding_window": false,
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| 74 |
"vocab_size": 151936,
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| 75 |
-
"attn_implementation": "sdpa"
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| 76 |
}
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| 72 |
"use_cache": false,
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| 73 |
"use_sliding_window": false,
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| 74 |
"vocab_size": 151936,
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| 75 |
+
"attn_implementation": "sdpa",
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| 76 |
+
"use_bidirectional_attention": true
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| 77 |
}
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