pplx-embed-v1-0.6b-onnx-int8-standard
Re-exports of perplexity-ai/pplx-embed-v1-0.6B (revision `2c4d510d`) with **standard ONNX operators**, usable by Transformers.js / ONNX Runtime Web (WASM and WebGPU) and ONNX Runtime Node. The official ONNX files use `GatherBlockQuantized`, which ORT Web cannot load. Pooling: masked mean over `last_hidden_state` (identical to the official `pooler_output`), then L2, then Matryoshka truncation to 256 dims and L2 again, as in the Deposium stack. Measurements: 38 texts in 6 languages (10 to 218 tokens) with ONNX Runtime 1.25 CPU, plus 8 texts (up to 512 tokens) in Chrome 152 with Transformers.js 4.3.0 / ORT Web 1.31-dev on an RTX 5060 (WebGPU) and on WASM. Full report, scripts and raw results: deposium-turbov3 `docs/2026-09-17-browser-embedding-t1-weight-only-reexport.md`.
翻訳準備中のため原文を表示しています
Re-exports of perplexity-ai/pplx-embed-v1-0.6B (revision `2c4d510d`) with **standard ONNX operators**, usable by Transformers.js / ONNX Runtime Web (WASM and WebGPU) and ONNX Runtime Node. The official ONNX files use `GatherBlockQuantized`, which ORT Web cannot load. Pooling: masked mean over `last_hidden_state` (identical to the official `pooler_output`), then L2, then Matryoshka truncation to 256 dims and L2 again, as in the Deposium stack. Measurements: 38 texts in 6 languages (10 to 218 tokens) with ONNX Runtime 1.25 CPU, plus 8 texts (up to 512 tokens) in Chrome 152 with Transformers.js 4.3.0 / ORT Web 1.31-dev on an RTX 5060 (WebGPU) and on WASM. Full report, scripts and raw results: deposium-turbov3 `docs/2026-09-17-browser-embedding-t1-weight-only-reexport.md`.
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