Modelpublic

Argo1-OOAS/TinyLlama-1.1B-V3-EdgeTravel

sourceHugging Faceapache-2.0updated 1mo agoView on Hugging Face

1likes173downloads

Model Card

Recommended Usage

For the easiest way to use this model with all required settings and its full functionality, use the TrajectoryLM application.

Screenshots

[image]

TinyLlama-1.1B V3 — edge/travel trigger

This model scales the contextual edge/travel trigger branch to a frozen TinyLlama-1.1B chat core. Only 16,781,313 branch parameters were optimized; the official Transformer weights remained unchanged. A trigger can activate the branch for a configurable number of following tokens, optionally conditioned on user text.

Property	Value
Total parameters	1,116,829,697
Trained branch parameters	16,781,313
Layers / width	22 / 2,048
Context length	2,048
Completed branch updates	2,000
Token presentations	262,144,000
Terminal sampled validation loss	0.5318 (PPL 1.7)

The validation figure is a terminal training-loop estimate for the selected branch lesson objective, not ordinary all-token TinyLlama perplexity.

UI usage

bash

git clone https://github.com/Argo1-OOAS/TrajectoryLM.git
cd TrajectoryLM

Run start_windows.ps1 on Windows or start_macos.command on macOS, following the TrajectoryLM README. The cross-platform launcher can fetch missing files with download progress. The UI highlights triggers and affected tokens and audits the branch-off versus final token choices. See research_paper.pdf for the complete report.

Limitations

Strong context guidance can damage fluency or cause trigger loops. The model is experimental, has no broad safety/capability evaluation, and must not be used as a reliable source for high-impact decisions.

Citation

bibtex

@misc{argo1ooas2026tinyllamav3,
 title={Scaling Trigger-Scoped Edge/Travel Adaptation to TinyLlama-1.1B},
 author={Argo1-OOAS}, year={2026},
 url={https://huggingface.co/Argo1-OOAS/TinyLlama-1.1B-V3-EdgeTravel}
}