perplexity-ai/pplx-embed-v2-late-0.6b
feature-extraction model by perplexity-ai
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Model card & documentation
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pplx-embed-v2-late: Multimodal Late-Interaction Embeddings pplx-embed-v2-late is a family of multimodal late-interaction (ColBERT) retrievers for text, images, and visual documents, built on Qwen3.5 with bidirectional attention. The models produce one 128-dimensional vector per token and score query–document similarity using MaxSim. The 0.6B and 9B models share an embedding space, allowing the 0.6B model to query an index built with the 9B model. For benchmarks and details, see our blog post. Both models were distilled from an internal 18B ColBERT teacher trained on pair and triplet data. Distillation used a token-level LEAF-style objective. The 0.6B model was fully fine-tuned. For the 9B model, the…
Read the full model card ↗ · Preview checked 2026-10-30T17:03:57.539Z
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Model overview
perplexity-ai/pplx-embed-v2-late-0.6b is a feature-extraction model repository published by perplexity-ai on Hugging Face. The source reports the sentence-transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- feature-extraction
- Library
- sentence-transformers
- Recent downloads (30 days)
- 1,146
- Cumulative likes
- 54
- Hugging Face trending score
- 54
- Reported safetensors parameters
- 594,321,600
- Architecture
- Qwen3_5Model
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2026-08-03T10:37:26.000Z
- Last modified
- 2026-10-08T14:34:03.000Z
Compatibility and lineage
Reported languages: multilingual
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-13T06:40:58.146Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.