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LibertAIDAI/deem-0.8-v1
deem-0.8-v1 is a machine learning model from LibertAIDAI. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for deem. The card lists the license as apache-2.0.
Decisions, anywhere. The full Deem decision stack on CPU — typed, calibrated choices, scores, and yes/no decisions with abstention, served by our own Rust runtime. No GPU required.
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From the Hugging Face model README
Decisions, anywhere. The full Deem decision stack on CPU — typed, calibrated choices, scores, and yes/no decisions with abstention, served by our own Rust runtime. No GPU required.
Update (v1.1): this release improves accuracy on temporal comparisons. v1.0 answered compact return-window questions ("order 60 days old" — "within the 30-day window?") from a yes-prior, and could rate P(within) + P(outside) up to 1.9. v1.1 trains the comparison itself across phrasings, with faithful verification traces: return-policy accuracy rises to 98.2% (from 96.6%), the window boundary is sharp (30 in / 31 out), and polarity consistency is exact — P(within) + P(outside) = 1.0 at every age. Standard-suite and hold-out scores hold steady. The v1.0 weights remain available under
v1.0/.
A single static Rust binary. No Python, no C++ dependencies at runtime.
vdpbf16ps) and int8
(vpdpbusd) GEMM lanes, ~3.4 TFLOPs/s isolated int8/v1/systemone — drop-in for the TypeSafe SDKgit clone https://github.com/Libertai/deem && cd deem/rust
cargo build --release
DEEM_CHECKPOINT=LibertAIDAI/deem-0.8-v1 ./target/release/deem-server
Runs where GPUs don't: CI runners, edge boxes, laptops, serverless micro-VMs.
Apache-2.0 (weights, code, and benchmark).