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learosema/
webbee-delegate-models

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WebBee Delegate Models

Fine-tuned T5-small models used by WebBee — a plain-English web development agent — for its Tier 2a inference pipeline.

Each model is an ONNX int8-quantised export of a T5-small checkpoint trained on synthetic data. They run locally via @xenova/transformers with no GPU required.

Models

`goal-to-steps/`

Decomposes a high-level development goal into a sequence of concrete WebBee commands. This is WebBee-specific: the model knows the agent's verb vocabulary (add, inject, install, add route, add hook, …) and the idiomatic step format used throughout the system.


Task	`text2text-generation`
Input	Natural-language goal (e.g. `"add authentication"`)
Output	Pipe-separated WebBee steps (e.g. `"add component LoginForm \| add hook useAuth \| add route api/auth"`)
Training examples	533 synthetic goal→steps pairs across 8 categories

Usage

import { pipeline } from '@xenova/transformers';

const generator = await pipeline(
  'text2text-generation',
  'learosema/webbee-delegate-models',
  { subfolder: 'goal-to-steps' }
);

const result = await generator('add authentication');
console.log(result[0].generated_text);
// → add component LoginForm | add hook useAuth | add route api/auth

Training

Models were trained and exported using the scripts in packages/delegate-model/ of the WebBee repository.

Base model: google/t5-small
Quantization: ONNX int8 via optimum

License

Apache 2.0 — same as the base T5-small model.