On-device LLMs &
AI SDK Provider

01import gerbil from "@tryhamster/gerbil/browser";
02
03// Load model (cached after first download)
04await gerbil.loadModel("smollm2-360m");
05
06// Power your UI with AI
07const suggestions = await gerbil.complete(userInput);
08const summary = await gerbil.summarize(longText);
09const category = await gerbil.classify(content, labels);
10
11// Streaming for chat UIs
12for await (const chunk of gerbil.stream(prompt)) {
13  updateUI(chunk);
14}

01import gerbil from "@tryhamster/gerbil";
02
03// Load larger model on server
04await gerbil.loadModel("qwen3-0.6b");
05
06// Generate with thinking mode
07const result = await gerbil.generate("Write a haiku", {
08  thinking: true,
09  maxTokens: 100,
10});
11
12console.log(result.thinking); // reasoning steps
13console.log(result.text);     // final response

01import { Gerbil } from "@tryhamster/gerbil";
02
03const g = new Gerbil();
04await g.loadModel("ministral-3b"); // Vision + reasoning
05
06// Describe any image
07const { text } = await g.generate("What's in this photo?", {
08  images: [{ source: "https://example.com/sunset.jpg" }]
09});
10
11// Compare images
12const diff = await g.generate("What changed?", {
13  images: [
14    { source: beforeScreenshot },
15    { source: afterScreenshot }
16  ]
17});

01import { defineTool } from "@tryhamster/gerbil";
02import { z } from "zod";
03
04const weather = defineTool({
05  name: "get_weather",
06  description: "Get weather for a city",
07  parameters: z.object({
08    city: z.string(),
09  }),
10  execute: async ({ city }) => {
11    return `Weather in ${city}: 72°F, sunny`;
12  },
13});
14
15// LLM can now call this tool during generation

01import { commit, summarize, review } from "@tryhamster/gerbil/skills";
02import { describeImage, captionImage } from "@tryhamster/gerbil/skills";
03
04// Generate commit message from staged changes
05const msg = await commit({ type: "conventional" });
06
07// Summarize any content
08const tldr = await summarize({ content: longDoc });
09
10// Vision skills
11const alt = await captionImage({ image: photoUrl });
12const analysis = await describeImage({ 
13  image: screenshot, 
14  focus: "text" 
15});

01import { Gerbil } from "@tryhamster/gerbil";
02
03const g = new Gerbil();
04
05// Generate speech with Kokoro-82M
06const result = await g.speak("Hello, I'm Gerbil!", {
07  voice: "af_heart",  // 28 voices available
08  speed: 1.0,
09});
10
11// result.audio = Float32Array (PCM samples)
12// result.sampleRate = 24000
13// result.duration = seconds
14
15// Or use the AI SDK
16import { experimental_generateSpeech } from "ai";
17const audio = await experimental_generateSpeech({
18  model: gerbil.speech(),
19  text: "Hello from Gerbil!",
20});

01import { Gerbil } from "@tryhamster/gerbil";
02import { readFileSync } from "fs";
03
04const g = new Gerbil();
05
06// Transcribe audio with Whisper
07const audioData = new Uint8Array(readFileSync("audio.wav"));
08const result = await g.transcribe(audioData, {
09  timestamps: true,  // Get word-level timing
10});
11
12console.log(result.text);
13// "Hello world, this is a test"
14
15// With timestamps
16for (const seg of result.segments) {
17  console.log(`[${seg.start}s] ${seg.text}`);
18}

$ gerbil "Write a haiku about coding"

🤖 Loading smollm2-360m...
✓ Model loaded (2.3s)

Silent keystrokes fall
Bugs emerge from tangled code  
Coffee saves the day

⚡ 47.2 tok/s | 0.8s

$ gerbil speak "Hello world" --voice bf_emma
$ gerbil transcribe audio.wav --timestamps
$ gerbil voice question.wav  # STT → LLM → TTS