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Canonical:kevinqz/Pulpie-Orange-Base-CoreAI— source of truth.
(input_ids, attention_mask) to
per-token logits. Produced by coreai-fabric and indexed by
coreai-catalog.Encoder, not a chat model. This is a single-forward classifier — no text generation, no KV-cache. The host owns the tokenizer (use the upstream tokenizer at feyninc/pulpie-orange-base), feeds token ids, and reads the per-token argmax.
| Field | Value |
|---|---|
| Parameters | 0.6B |
| Architecture | transformer |
| Capabilities | token-classification |
| Labels | 2 |
| Sequence length | 64 (static) |
| Quantization / precision | none / float32 |
| On-disk size | 2.3 GB |
| Asset kind | single-graph encoder ((input_ids, attention_mask) -> per-token logits) |
| assetVersion | 2.0 |
(input_ids, attention_mask) in →
per-token logits out. You supply the upstream tokenizer and the argmax /
label mapping in your host code (Swift or Python). Token ids are int32 at the
graph boundary; pad or truncate to the static sequence length (see Model facts).pip install coreai-catalog && coreai-catalog install pulpie-orange-baseminimum_os v27,
so the on-device Swift runtime requires macOS/iOS 27+. A Mac on macOS 26 can
convert and inspect it but not run it on-device.(input_ids, attention_mask), measured on apple_silicon. The encoder analog of the LLM logit-parity: it certifies the export computes the SAME per-token logits as the source — a conversion-fidelity metric, not task accuracy.coreai-fabric verify.| Field | Value |
|---|---|
| Base model | feyninc/pulpie-orange-base @ d8f4eaabc8647b96034b906ab3864572e1489c10 |
| Converted by | models/eurobert/export.py (version not reported) |
| Recipe | pulpie-orange-base (recipe_source: fabric) |
| Precision / quantization | float32 / none |
| Conversion date | 2026-07-07 |
LICENSE. This artifact is a converted derivative of the base model: its
weights were converted to Apple Core AI format. The conversion itself is
community work.pulpie-orange-base.aimodel pipeline that produced this asset.