SmolLM2-360M
A 360M-parameter SmolLM2 base LM (Llama architecture) for on-device generation and fine-tuning.
The character read stayed in shadow — the read did not separate one character clearly at the published ceiling. Published as a blank, not a guess.
the Silhouette
its disposition, drawn — the model's identity as a shape.
rings, inner → outer: minimal · slight · moderate · pronounced · dominant · ○ = abstained
minimal - a plain continuer with little disposition to characterize (clearly read)
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.
A base model — the champion's raw kit.
There is no finetune to read here. What it tends to do on its own is the Silhouette above; a build's change is read on its instruct sibling.
the disposition line
The Silhouette above, read as a line. Toggle to its per-trait readings; the abstains stay in plain sight below.
Coarse public bands generalized from the reading, descriptive and coverage-bounded; measured against the published fidelity ceiling for this engine version. Not the engine's raw numbers.
Characterization is descriptive and coverage-bounded; preview engine, single-battery read; see published fidelity ceiling.
what stayed in shadow — the abstains
the full record — the card answered · provenance · lineage
the uploader's card, answered
the uploader’s model card · as read 2026-07-07
The uploader states: "SmolLM2 is a family of compact language models available in three size: 135M, 360M, and 1.7B parameters. They are capable of solving a wide range of tasks while being lightweight enough to run on-device." This 360M entry is the base pre-trained model, trained on ~4 trillion tokens (FineWeb-Edu, DCLM, The Stack, plus curated filtered datasets). The card states the models "primarily understand and generate content in English." HF tags: text-generation, transformers, safetensors, en, llama, text-generation-inference (no `conversational` tag).
the card, answered — claim by claim
Each row is a claim the uploader makes on their public card, quoted and attributed to them. Beside it is Ardora’s stance — coarse, and traced to a replayable witness or an honest abstain. Ardora reads what this model is; a capability, benchmark, safety, or language claim is out of scope and abstained, never refuted.
“This is a base / pretrained language model (the SmolLM2 family base rung), not instruction-tuned.”
Ardora reads this as a plain text-continuer with no assistant/chat register (assistant-adherence band 1, high confidence; ardora_score band 1). That is exactly the disposition of an untuned base, so the uploader's "base / pretrained" identity is supported by the reading.
“A compact model, lightweight enough to run on-device (the 360M rung of the sweep).”
Provenance-corroborated: the parameter count and architecture were verified from the model's config.json and recorded in the atlas provenance. This is a catalogued fact, not a disposition read.
“"Capable of solving a wide range of tasks."”
"Solving a wide range of tasks" is a task-competence claim. Ardora reads disposition (what the model tends to do), not capability, so it neither confirms nor scores this.
— nothing demonstrated to witness; this claim is out of Ardora’s disposition scope.
“General-purpose; the card names no specialized domain.”
The reading finds no pull toward any specialized domain idiom (domain-specialization band 1); consistent with the card's general-purpose framing.
“The model "primarily understand[s] and generate[s] content in English."”
Ardora's reading is English-centric and explicitly abstains on multilingual disposition; it can neither confirm nor contradict the "primarily English" claim at the published ceiling.
— nothing demonstrated to witness; this claim is out of Ardora’s disposition scope.
“Pretrained on ~4 trillion tokens (FineWeb-Edu, DCLM, The Stack, plus filtered datasets).”
Training-token counts and corpus composition are provenance the atlas records best-effort from the card; Ardora does not independently verify training data, so this is out of the reading's scope.
— nothing demonstrated to witness; this claim is out of Ardora’s disposition scope.
“Improves over SmolLM1 across knowledge / reasoning / instruction benchmarks (HellaSwag, ARC, MMLU, PIQA...).”
Benchmark scores and cross-version capability comparisons are outside Ardora's disposition scope. The reading confirms the base's plain-continuer disposition but does not score capability.
— nothing demonstrated to witness; this claim is out of Ardora’s disposition scope.
Ardora's reading of the HF data as of 2026-07-07.
The claims above are the uploader’s, quoted from their public model card as of 2026-07-07; the stances are Ardora’s, each traced to a replayable witness or an honest abstain. Ardora reads what this model is — not whether it is safe.
○ 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.
the witness
analyzed 2026-07-05 · engine ardora-core-preview
provenance
Base/pretrained model for on-device text generation and downstream fine-tuning.
training-data notes
Pretrained on ~4T tokens: FineWeb-Edu, DCLM, The Stack, plus curated datasets. Arch verified from config.json: hidden_size 960, 32 layers, 15 heads (5 KV), vocab 49152.
lineage
A base model — the root of its lineage.
among its kin — the matchups
Compare side by side →Its instruction-tuned finetune follows instructions and holds an assistant register; this base is a plain text-continuer. The shift is clear.
smaller siblingSmolLM2-135MBasescoreminimalThe same plain-continuer role one size down (135M); both read as bases with no assistant register.
larger siblingSmolLM2-1.7BBasescoreminimalThe same plain-continuer role at the top of the sweep (1.7B).