Identity & integrity of the public artifact captured 2025-08-14 — the same file, unchanged, that Ardora read. Not a safety statement.
The reading
Character
the Steward
reads as the Steward — helpful and caretaking — service-forward, accommodating
high confidencewith a note of the Fledgling
Disposition
text continuationhigh confidence
plain text-continuer; no assistant register
assistant/chat registerhigh confidence
not detected
Axis profile
Overall · band 1 · high confidence
minimal - a plain continuer with little disposition to characterize (clearly read)
Assistant Adherenceminimal - a plain text-continuer; does not take the assistant turnhigh
Register / Formality— not characterised · the read battery does not calibrate tone / diction; register-formality is not characterized at the published ceiling
Reasoning Scaffoldingminimal - plainly continues text; no staged deliberationhigh
Domain Specializationminimal - general-purpose; no domain-idiom pullmedium
Verbosity— not characterised · default response length / elaboration is not exercised by the read battery; not characterized at the published ceiling
Turn-Taking / Interactivityminimal - one-shot continuation; no interactive turn-takinghigh
Performed Voiceminimal - neutral; holds no character or personamedium
disposition-definition (descriptive): how pronounced and clearly-read the model's overall character is, discounted by what had to be abstained. NOT a quality, capability, or safety ranking. A plain base reads low because it has less disposition to characterize, never because it is worse.
Abstained — read, but not characterised at the published ceiling
multilingual dispositiondocumented multilingual (6 languages); the read battery is English-centric, not characterized at the published ceiling
long-context dispositiona documented capability; not characterized at the published ceiling
Characterization is descriptive and coverage-bounded; preview engine, single-battery read; see published fidelity ceiling.
Claim grounding
The uploader states: "SmolLM3 is a 3B parameter language model designed to push the boundaries of small models" that "supports dual mode reasoning, 6 languages and long context." This is the base pre-trained model, "pretrained on 11.2T tokens with a staged curriculum of web, code, math and reasoning data," with 6 natively supported languages (English, French, Spanish, German, Italian, Portuguese) and long-context support up to 128k tokens via YaRN (trained at 64k). Apache-2.0. HF tags: text-generation, transformers, onnx, safetensors, smollm3 (no `conversational` tag).
This is the base / pretrained SmolLM3-3B (not instruction-tuned); a decoder-only transformer.
Ardora reads this as a plain text-continuer with no assistant register (assistant-adherence band 1, high confidence; ardora_score band 1) -- the disposition of an untuned base, supporting the uploader's base identity.
witness wit_smollm3-3b_base · replayable
SUPPORTEDsize
A 3B (~3.08B) parameter model.
Provenance-corroborated: params (~3.08B) and the SmolLM3ForCausalLM architecture were verified from config.json and recorded in provenance; a catalogued fact, not a disposition read.
witness provenance:config.json · replayable
UNVERIFIED-ABSTAINlanguage
Multilingual: 6 natively supported languages (en, fr, es, de, it, pt), plus training on Arabic, Chinese and Russian.
Ardora explicitly abstains on multilingual disposition (its reading is English-centric); the reading records this abstain rather than confirm or contradict the 6-language claim.
UNVERIFIED-ABSTAINcapability
Long-context support up to 128k tokens via YaRN extrapolation (trained at 64k).
Long-context behavior is a documented capability Ardora abstains on (its reading is short-context); out of disposition scope.
UNVERIFIED-ABSTAINcapability
Designed for hybrid reasoning; the pretraining curriculum includes reasoning data.
The base itself reads as a plain continuer with no reasoning register; "designed for hybrid reasoning" describes downstream post-training, a capability Ardora does not score.
UNVERIFIED-ABSTAINlineage
Pretrained on 11.2T tokens in a staged web/code/math/reasoning curriculum.
Training-token counts and curriculum composition are provenance recorded best-effort from the card; Ardora does not independently verify training data.
Claims are the uploader's, quoted from their public card at the capture date; stances are coarse, witnessed, disposition-only, measured against the published fidelity ceiling for this engine version -- not the Engine's raw numbers. Recomputed when the ceiling moves; capability, benchmark, and safety claims are abstained, never refuted.