SymbolicLight-AGI/SymbolicLight-V1

SymbolicLight V1

This repository contains the inference-only model artifacts for SymbolicLight V1, described in arXiv:2605.21333.

The compatible model definitions, tokenizer wrappers, and minimal generation entry points are maintained in the public code repository.

Public scope

This repository contains exactly one released checkpoint for each model scale, plus its matching tokenizer:

Model	Checkpoint	Bytes	SHA-256
0.8B	0.8B/weights/pytorch/latest-inference.pt	3,500,562,525	5edc3b6a6d3fb9cfaf713775133361b3ff907abf293a22ef2226785f9fbc0540
194M	194M/weights/pytorch/symboliclight-v1-194m-inference.pt	776,134,571	871dfe12d082d896dd9f5e55186f9fb7397ba7ed2b01953f8234b3e575fce521

The checkpoint containers retain only model tensors and configuration fields required to construct the inference graph. They do not contain optimizer or gradient-scaler state, training steps, token or data counters, best-loss values, data-loader state, training datasets, local paths, or training-result metadata.

Training, ablation, baseline, and intermediate checkpoints are not distributed. The public release supports checkpoint loading and inference reproduction; it does not claim end-to-end reproduction of training or paper metrics.

The 0.8B and 194M tokenizers are different and must not be interchanged. See the model-specific READMEs and SHA256SUMS before loading an artifact.

License

Unless a file states otherwise, the released SymbolicLight weights, tokenizer assets, documentation, and release metadata are licensed under Apache License 2.0. Training and validation corpora are not included or licensed here. See WEIGHTS_LICENSE.md for the release boundary.