AI가 움직이고 미래가 업데이트됩니다.PII-Tracer-MLX
MLX weights for PII-Tracer, a PII masking model for conversational data. The model uses a ~600M-parameter bidirectional Qwen3 encoder with a `perplexity-ai/pplx-embed-v1-0.6b` backbone and two heads: The backbone's linear projections use **8-bit affine quantization with group size 64**. Embeddings and normalization weights remain bf16; both heads remain fp32. The weights file is approximately 779 MB. Quantized projections retain the `backbone.*` key names and store packed `uint32` `weight` tensors with bf16 `scales` and `biases`. The unquantized heads use `token_cls_head.*` and `sensitivity_head.*`.
번역 준비 중입니다. 원문을 표시합니다.
MLX weights for PII-Tracer, a PII masking model for conversational data. The model uses a ~600M-parameter bidirectional Qwen3 encoder with a `perplexity-ai/pplx-embed-v1-0.6b` backbone and two heads: The backbone's linear projections use **8-bit affine quantization with group size 64**. Embeddings and normalization weights remain bf16; both heads remain fp32. The weights file is approximately 779 MB. Quantized projections retain the `backbone.*` key names and store packed `uint32` `weight` tensors with bf16 `scales` and `biases`. The unquantized heads use `token_cls_head.*` and `sensitivity_head.*`.