Timmy T2 stands for Timmy Timer Translator. It is a tiny, browser-first seq2seq model for translating natural-language timer requests into Timey's compact action DSL.
This is not a new foundation architecture. It is a task-specific fine-tuned T5-style encoder-decoder model plus a compact output language, lossless slot-annotated input format, constrained parser, and browser ONNX runtime package.
Release
Version: v0.1.0
Runtime model version: phase4y-actions-browser-exact-checkpoint-50-dynq8enc-q4dec-ort-beam4
Timmy T2 is intended for Timey-style timer planning:
5 one minute timers and one 30 second
The model emits action commands over extracted slot ids:
text
1REP C0 A0
2ADD A1
3END
The application parses those commands into concrete timers deterministically.
Files
Root files are the fp32/safetensors checkpoint for Python Transformers.
browser/ contains the production browser artifact:
dynamic q8 encoder ONNX
q4 decoder ONNX
tokenizer/config files used by the Timey browser runtime
eval/ contains release evaluation summaries.
release_manifest.json records hashes, sizes, evals, and production smoke checks.
Training Data
Public dataset rows:
Split
Rows
train
2639
validation
207
hard_validation
62
all_public
2846
The 16-row hidden validation split is withheld from the public dataset to preserve a private holdout.
Evaluation
Eval
Records
Parseable
Strict exact
Semantic exact
Semantic invalid
onnx-dynq8enc-q4dec-validation
207
100%
100%
100%
0%
onnx-dynq8enc-q4dec-hard
62
100%
100%
100%
0%
onnx-dynq8enc-q4dec-hidden
16
100%
100%
100%
0%
onnx-dynq8enc-q4dec-browser-failures
3
100%
100%
100%
0%
fp32-validation
207
100%
100%
100%
0%
fp32-hard
62
100%
100%
100%
0%
fp32-hidden
16
100%
100%
100%
0%
Browser Smoke
The deployed production browser runtime was smoke-tested with service workers enabled. It loaded timey-t5-efficient-tiny and produced the expected timer sequences for:
5 one minute timers and one 30 second -> [60, 60, 60, 60, 60, 30]
first and last timer 5 minute, 5 one minute timers in between -> [300, 60, 60, 60, 60, 60, 300]
Limitations
This is a narrow task model for timer requests, not a general assistant.
It expects Timey's lossless slot-annotated input format at inference time.
Correction/edit requests are intentionally handled by deterministic fallback logic in the app.
Public validation is synthetic and task-targeted; broader natural user traffic should be evaluated before expanding claims.
