Haste Jev 10m (Large)

Role: Richer multimodal state

Open-weights System-1 decision engine for software paths that need typed decisions under a time budget (agent routing, tool routing, intent classification, pre-flight guardrails, browser action selection). Not a chat model.

Measured specification

Field Value
Total parameters 10,002,275
Trainable parameters 6,856,675
Hash-table buffers 3,145,600
d_model 320
Layers 5
Heads 4

Parameter counts match the GitHub README table (verified with verify_claims.py).

Honest claims

Claim Status
PICA option-order bias = 0.0% Verified architecturally
Exact parameter table Verified
FP32 ~0.4 MB for 100k weights Verified (weight storage only)
p99 < 15ms / ECE < 0.009 / 99.4% arithmetic Not verified — do not cite from this card
Published latency / accuracy on your workload Measure yourself

Weights may be lightly or untrained prototypes depending on export; treat behavioral accuracy as unknown until you evaluate on labeled data.

Quickstart

from hastejev import HasteJevEngine

eng = HasteJevEngine.from_pretrained("noffy/hastejev-10m")
# eng = HasteJevEngine.from_pretrained("noffy/hastejev-10m", quantization="int4")

r = eng.choice(
    "Request: reset password for user@corp.example",
    ["auth_self_service", "billing", "security_review"],
)
print(r.decision, r.confidence)

Install: pip install git+https://github.com/racstan/hastejev.git

Files

File Contents
model.safetensors / pytorch_model.bin FP32 state dict
model_fp16.safetensors FP16
model_int8.safetensors True weight-only int8 (weight_q) when re-exported with ≥1.1.0
model_int4.safetensors True packed int4 (weight_packed) when re-exported with ≥1.1.0

Older revisions of model_int8/model_int4 may be mislabeled FP32; re-export or re-download after this commit.

License

Apache-2.0

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