vh
a6c1d3c454
A/B of the live STT seat (fv-ml1 GPU 0, sherpa-onnx int8 v3) against nvidia/parakeet-unified-en-0.6b, measured on GPU 3 with the seat's own image, k2-fsa's published unified int8 export, fp32/fp16 exports made with k2-fsa's recipe, v2 int8, and NeMo 3.0.0 (fp32, bf16 autocast, bf16 weights). - Seat int8 graph runs on one CPU thread (cpu/wall 1.00, GPU 2-9%). - unified-en under NeMo: -121/-234/-530 ms vs the seat at 1-3/3-8/8-20 s (paired, n=120/bin; floor <=6 ms; +50 ms positive control reads +52-54). - unified-en WER lower in every runtime: -0.7 pp clean, -1.5 pp other, -3.2 to -4.4 pp AMI (paired CIs exclude 0). - Seat defects found: hard 400 s input ceiling (HTTP 500), truncation after a quiet 1.5 s pause, and severe long-window dropouts (int8 v3 only). - B-bf16w needs +0.8 to +1.5 GB over the seat's 1,690 MiB on GPU 0. Raw requests, hypotheses, manifests and the full harness under services/parakeet-ab-2026-09-30/. No deploy; live seat untouched apart from 240 light test requests.
42 lines
2.5 KiB
Python
42 lines
2.5 KiB
Python
"""Fetch pinned artifacts; verify each against its published digest. Prints a provenance line per file."""
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import hashlib, json, os, sys, urllib.request
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TOKEN = open("/tank/aimodels/huggingface/token").read().strip()
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DL = "/tank/spikes/parakeet-ab/dl"
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def sha256(p):
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h = hashlib.sha256()
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with open(p, "rb") as f:
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for b in iter(lambda: f.read(1 << 24), b""): h.update(b)
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return h.hexdigest()
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def fetch(url, out, auth=False):
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if os.path.exists(out): return
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req = urllib.request.Request(url, headers={"Authorization": f"Bearer {TOKEN}"} if auth else {})
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with urllib.request.urlopen(req, timeout=120) as r, open(out + ".part", "wb") as f:
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while True:
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b = r.read(1 << 22)
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if not b: break
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f.write(b)
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os.rename(out + ".part", out)
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prov = []
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# GitHub release assets (digest from the GitHub API, recorded 2026-09-30)
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gh = {"sherpa-onnx-nemo-parakeet-unified-en-0.6b-int8-non-streaming.tar.bz2": "99f63605b3a85a54c250c0869670a687b7d6598a47bf2421515e1f839a76e150",
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"sherpa-onnx-nemo-parakeet-tdt-0.6b-v2-int8.tar.bz2": "157c157bc51155e03e37d2466522a3a737dd9c72bb25f36eb18912964161e1ad"}
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for name, want in gh.items():
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out = f"{DL}/{name}"
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fetch(f"https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/{name}", out)
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got = sha256(out)
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prov.append(dict(src=f"github:k2-fsa/sherpa-onnx@asr-models/{name}", sha256=got, expected=want, ok=got == want))
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# HF datasets, revision-pinned; expected sha = LFS oid from the authenticated API
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hf = [("openslr/librispeech_asr", "71cacbfb7e2354c4226d01e70d77d5fca3d04ba1", ["all/test.clean/0000.parquet", "all/test.other/0000.parquet"]),
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("edinburghcstr/ami", "46f28f2503e2ec48f8867a84eef356c70476beab", [f"ihm/test-0000{i}-of-00004.parquet" for i in range(4)])]
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for repo, rev, files in hf:
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req = urllib.request.Request(f"https://huggingface.co/api/datasets/{repo}/revision/{rev}?blobs=true", headers={"Authorization": f"Bearer {TOKEN}"})
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meta = json.load(urllib.request.urlopen(req, timeout=60))
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oid = {s["rfilename"]: (s.get("lfs") or {}).get("sha256") for s in meta["siblings"]}
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for fn in files:
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out = f"{DL}/{repo.replace('/', '__')}__{fn.replace('/', '__')}"
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fetch(f"https://huggingface.co/datasets/{repo}/resolve/{rev}/{fn}", out, auth=True)
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got = sha256(out)
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prov.append(dict(src=f"hf-dataset:{repo}@{rev}/{fn}", sha256=got, expected=oid.get(fn), ok=got == oid.get(fn)))
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for p in prov: print(json.dumps(p))
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json.dump(prov, open("/tank/spikes/parakeet-ab/out/provenance-fetch.json", "w"), indent=1)
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