metadata
language: en
license: apache-2.0
tags:
- webbee
- code-generation
- text2text-generation
- t5
- onnx
datasets:
- synthetic
pipeline_tag: text2text-generation
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.