speaker-diarizationautomatic-speech-recognition# HF card front matter pipeline_tag · family: wespeaker
| Source | https://huggingface.co/litert-community/Speaker-Diarization-LiteRT |
|---|---|
| License | mit |
| Model file | 1c2f09bf17c4dc60dd830c02be355beb4a0042351bc6f6ebdb71957dde613e24.tflite — downloaded from the source at runtime; this site hosts no weights |
Preparing…
Every number is labeled with the environment that produced it — headless desktop Chromium is not a user’s phone, and results are only meaningful together with their environment.
| Backend | Status | Full delegation | Output match | Latency p50 (ms) | Environment | Verified | Provenance |
|---|---|---|---|---|---|---|---|
wasm_xnnpack | pass | — | — | 1399.142 | mac-studio-m4-max · chromium 151.0.7922.34 headless · macOS · @litertjs/core 2.5.3 | 2026-08-11 | measured |
webgpu_mldrift | pass | yes | pass | 3.852 | mac-studio-m4-max · chromium 151.0.7922.34 headless · macOS · @litertjs/core 2.5.3 | 2026-08-11 | measured |
Full record (failure class, evidence, sweep config): raw sweep JSON · card.json · CARD.md
One-line prompt for your AI coding assistant (uses the litert-cookbook web skill):
Use the litert-cookbook web skill to build a LiteRT.js browser demo for speaker-diarization: load the model from https://huggingface.co/litert-community/Speaker-Diarization-LiteRT/resolve/main/1c2f09bf17c4dc60dd830c02be355beb4a0042351bc6f6ebdb71957dde613e24.tflite (license: mit) and run it with @litertjs/core.
One-line prompt for Claude Code / Gemini CLI — re-runs the same sweep verification for this model, locally:
In the edge-compat repo, verify speaker-diarization with the sweep harness: write /tmp/catalog.csv with the header line model_id,source,input_spec,license,notes and the single row speaker-diarization,https://huggingface.co/litert-community/Speaker-Diarization-LiteRT/resolve/main/1c2f09bf17c4dc60dd830c02be355beb4a0042351bc6f6ebdb71957dde613e24.tflite,1x500x80:float32,mit, — then run: cd web/sweep && npm ci && npm run sweep -- --catalog /tmp/catalog.csv --out out/ — and compare out/speaker-diarization.json with the sweep table on this page.