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@@ -11,7 +11,10 @@ tags:
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  pipeline_tag: token-classification
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  ---
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- # pplx-pii-masking
 
 
 
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  PII masking model for conversational data. A ~600M-parameter bidirectional
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  Qwen3 encoder
@@ -34,7 +37,7 @@ backbone, run encoder-only via `is_causal=false`) with two heads:
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  from transformers import AutoModel
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  model = AutoModel.from_pretrained(
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- "perplexity-ai/pplx-pii-masking", trust_remote_code=True
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  )
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  text = ("Hi, I'm Daniel Whitfield, you can reach me at "
@@ -77,15 +80,29 @@ config, including `"is_causal": false` for bidirectional attention.
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  ## Alternative packagings
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- - **vLLM:** [perplexity-ai/pplx-pii-masking-vllm](https://huggingface.co/perplexity-ai/pplx-pii-masking-vllm)
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  repackages the weights for token classification serving, with a scoring
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  adapter and a decoding client.
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- - **GGUF:** [perplexity-ai/pplx-pii-masking-GGUF](https://huggingface.co/perplexity-ai/pplx-pii-masking-GGUF)
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  provides an f16 backbone for llama-server, fp32 heads, and a self-contained
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  decoding client.
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- - **MLX:** [perplexity-ai/pplx-pii-masking-MLX](https://huggingface.co/perplexity-ai/pplx-pii-masking-MLX)
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  provides 8-bit converted projection weights for MLX. An MLX implementation
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  of the bidirectional encoder and two heads is required; a loader is not
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  included in that repository.
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  See each repository for its inference requirements and limitations.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  pipeline_tag: token-classification
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  ---
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+ # PII-Tracer
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+
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+ This repository provides PII-Tracer, the detector introduced in
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+ [PII-TRACE](https://arxiv.org/abs/2609.22200).
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  PII masking model for conversational data. A ~600M-parameter bidirectional
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  Qwen3 encoder
 
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  from transformers import AutoModel
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  model = AutoModel.from_pretrained(
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+ "perplexity-ai/PII-Tracer", trust_remote_code=True
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  )
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  text = ("Hi, I'm Daniel Whitfield, you can reach me at "
 
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  ## Alternative packagings
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+ - **vLLM:** [perplexity-ai/PII-Tracer-vLLM](https://huggingface.co/perplexity-ai/PII-Tracer-vLLM)
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  repackages the weights for token classification serving, with a scoring
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  adapter and a decoding client.
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+ - **GGUF:** [perplexity-ai/PII-Tracer-GGUF](https://huggingface.co/perplexity-ai/PII-Tracer-GGUF)
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  provides an f16 backbone for llama-server, fp32 heads, and a self-contained
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  decoding client.
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+ - **MLX:** [perplexity-ai/PII-Tracer-MLX](https://huggingface.co/perplexity-ai/PII-Tracer-MLX)
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  provides 8-bit converted projection weights for MLX. An MLX implementation
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  of the bidirectional encoder and two heads is required; a loader is not
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  included in that repository.
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  See each repository for its inference requirements and limitations.
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+
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+ ## Citation
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+
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+ If you use or reference this work, please cite:
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+
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+ ```bibtex
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+ @article{zhang2026piitrace,
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+ title = {{PII-TRACE}: A Benchmark for Context-Aware {PII} Detection in Multi-Turn {LLM} Conversations},
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+ author = {Zhang, Kaiyuan and Wang, Chuan and Zhong, Joey and Fryzel, Paul and Polley, Kyle and Ma, Jerry and Li, Ninghui},
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+ journal = {arXiv preprint arXiv:2609.22200},
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+ year = {2026},
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+ url = {https://arxiv.org/abs/2609.22200}
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+ }
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+ ```