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vh de6ea32f34 feat(parakeet-nemo): speech seat moves to parakeet-unified-en under NeMo (bf16 weights)

Prime-approved switch of the fleet STT seat (fv-ml1 :8300, LiteLLM ext-stt/
whisper-1, caller talk) from the sherpa-onnx int8 seat to arm B-bf16w of the
2026-09-30 A/B (docs/pfi/parakeet-seat-ab-2026-09-30.md): p50 33/36/42/71 ms
vs the old seat's 187/308/626 measured on the same card today, WER 1.965/3.026
vs the A/B floor 1.97/3.09. All three seat defects fixed: 12-min file 200s
(windowed at 360 s after a GPU 0 OOM on one whole request; the A/B's own
long-form method), no pause truncation, no long-form dropout.

GPU 0 room: gen-small --gpu-memory-utilization 0.48 -> 0.36 (0.46 and 0.40
refuse their boot check; cyberprev+voices hold the card). Its KV is byte-
pinned, so the boot log is token-identical: 670,142 tokens / 2.56x before
and after. Seat rests 2,088 MiB; GPU 0 keeps ~1.9 GB free.

Two runtime landmines documented in the README: NeMo's attention mask is
materialised T x T even under local attention (hence the window), and
httptools 0.8.0 writes a NUL into the HTTP status line that httpx — i.e.
LiteLLM — rejects, so the image ships plain uvicorn with --http h11.

Old seat stopped, not removed: docker stop parakeet-nemo && docker start
parakeet is the rollback.

License: NVIDIA Open Model License (accepted by Prime 2026-09-30); note in
stacks/parakeet-nemo/README.md.

2026-10-01 01:32:48 -07:00

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parakeet-nemo — the fleet speech seat (parakeet-unified-en under NeMo)

STT seat on fv-ml1, port 8300, behind LiteLLM as ext-stt / whisper-1; the caller is talk. Switched over from the sherpa-onnx int8 seat (stacks/parakeet) on 2026-09-30 on Prime's order, after the A/B in docs/pfi/parakeet-seat-ab-2026-09-30.md (arm B-bf16w won: p50 23/27/33 ms vs the old seat's 144/260/565 ms at 1–3/3–8/8–20 s, lower WER on every set).

Why this runtime

The old seat was slow because of its RUNTIME: the int8 ONNX graph ran on one CPU thread. The defects it carried — HTTP 500 above ~400 s of audio, long-form dropouts, utterance truncation after a 1.5 s digital-silence pause — are all int8-export behaviours. This seat runs the model under NeMo torch with bf16 weights, full-precision mel front end, and NeMo's local-attention long-audio mode (±128), which is what removes all three defects.

Hard-wired seat invariants (app.py — each one is load-bearing, do not "clean up")

bf16 cast BEFORE .to("cuda") — restoring fp32 onto the GPU and casting there spikes the load by ~1.5 GB. GPU 0 cannot absorb that; it is shared with two vLLM seats.
Warm-up at the longest served length — the CUDA-graph greedy decoder costs ~330 ms extra on the first call at a new maximum length. The entrypoint warm-up runs ascending silent clips (WARMUP_SECONDS, default 1,8,60).
rel_pos_local_attn ±128 — a 30-minute file transcribes in ~2.6 s in ONE request; memory grows linearly in length instead of quadratically.
dither = 0.0 — dither is a training-time augmentation; it makes identical files decode differently call to call.
NeMo 3.0.0 is a floor — released 2.7.3 lacks this encoder's att_chunk_context_size.
No httptools; --http h11 is explicit. httptools 0.8.0 (pulled by uvicorn[standard], and auto-selected by uvicorn when importable) writes a NUL into the response status line — HTTP/1.1 200\x00OK — that h11/httpx reject with RemoteProtocolError: illegal status line. curl tolerates it; LiteLLM reaches this seat via httpx, so every consumer would break. Proven A/B on the same image: --http h11 clean, --http httptools dirty (2026-10-01). The image installs plain uvicorn==0.53.0 for exactly this reason.

License

nvidia/parakeet-unified-en-0.6b is distributed under the NVIDIA Open Model License Agreement (commercial/non-commercial use permitted; Prime accepted the terms 2026-09-30). This replaces the CC-BY-4.0 terms of the previous seat's weights for this service. Internal use: no NOTICE file required; keep this section as the license note. Weights pinned at HF revision fe53cd885760c96b6a5f51a0bfd362cb4584a98b (sha256 ec23ed91…), mounted read-only from /tank/aimodels/huggingface, HF_HUB_OFFLINE=1.

GPU 0 room

The seat rests ~2.5 GB, serves to ~2.8 GB, loads under ~3.0 GB (measured on GPU 0 at cut-over; see the ops log). Room was taken from vllm-gen-small: --gpu-memory-utilization 0.48 → 0.46 (its .env), KV cache and concurrency re-read from its boot log at each change. ⚠ util does NOT predict resident VRAM — after any gen-small restart, measure nvidia-smi Free on GPU 0 before believing the fraction. GPU 1 is NOT an option: its free memory is intern-decision's 32k headroom.

Rollback

The old seat was STOPPED, not removed: docker stop parakeet-nemo && docker start parakeet restores the sherpa seat on :8300 exactly as before (container and image both kept).

Deploy

Build on fv-ml1 in a versioned dir under /opt/docker/src/ (house convention), tag local/parakeet-nemo:nemo-X.Y.Z, point .env at it, docker compose up -d. Acceptance harness and the A/B's paired latency/WER tooling: /tank/spikes/parakeet-ab on fv-ml1 (do not delete).

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