# Sprig v0.1.0

Stage: **research baseline**. Not published to npm or Maven.

Authored English topic sentences; last two per topic held out. Six fixed categories.

## Artifact

- Raw bytes: 32065
- SHA-256: `040bbf25067e2b3efac9f8767e07fcd03c2bd4401466c3c44797591e5f9abe00`
- Training examples: 48
- Internal held-out smoke test: 9/12
- Classes: Technology, Science, Finance, Sports, Arts, Everyday

The internal test is not an independent real-world benchmark. Scores are uncalibrated. Artifact size excludes the runtime and memory overhead.

## Node / browser

From the repository root: `bun install && bun run sdk:build`.

```ts
import { createModel } from '@embermote/sprig';
const model = createModel();
```

Text models accept a string. Audio models accept `audioFeatures(pcm, 8000)`; Glyph accepts `shapeFeatures(points)`, both exported by `@embermote/core`.

## Kotlin

```kotlin
import dev.embermote.sprig.Sprig
val model = Sprig.load()
```

JDK 17+, root Gradle build. Model resources are bundled in each model module. Use `Features.audio` or `Features.shape` for numeric inputs. Android device testing is pending.

## Rebuild

`bun run train` uses the original recipe in `training/train.py`. No external datasets or third-party weights are downloaded.