TMCRA TokenGraph-LLM Stage C / Dynamic Token Graph Decoder V3
This release provides the Stage C public model package for TMCRA TokenGraph-LLM. Release assets are model artifacts only. Algorithm source, graph builders, full-chain training scripts, and evaluation templates are maintained in the GitHub source repository on main.
Source repository: https://github.com/reshuibuduo/TMCRA-TokenGraph-LLM
Hugging Face model page: https://huggingface.co/2009YU/TMCRA-TokenGraph-LLM
Model
- Asset:
tmcra_tokengraph_stagec_model_package_20260606.zip - SHA256:
cc23285628eaed47c20009b6be6b5eb0600ded57ac2e09519370d97158fecd33 - Checkpoint:
token_graph_dynamic_decoder_v3.pt - Parameters: about
114.6M - Architecture:
dim=512,graph_layers=8,decoder_layers=10, untied embeddings - Training: bf16, about 1.03M effective token-graph samples, 62,000 steps
Package contents
checkpoint/token_graph_dynamic_decoder_v3.ptdataset_metadata/tokenizer.jsondataset_metadata/manifest.jsontraining_summary_stagec_public.jsondocs/technical overview and smoke benchmark notesSHA256SUMS.txt
Full-chain source update
The source repository now includes:
- open-corpus schema2 conversion scripts;
- optional semantic teacher annotation scripts;
- token graph dataset builders;
- Stage C full-chain and sharded training templates;
- graph ablation and token attribution evaluation.
Start with:
docs/FULL_CHAIN_TRAINING.mddocs/FULL_CHAIN_TRAINING_ZH.mdscripts/run_stagec_full_chain_template.shscripts/run_stagec_sharded_training_template.sh
Smoke results
- Stage C normal: total loss
6.512117, lm loss4.641285 - Stage C no_edges: total loss
8.310654, lm loss5.790666 - Stage C shuffle_edges: total loss
7.702783, lm loss5.169387 - TinyStories smoke: normal avg words
73.88 - BLiMP smoke: 59%-64% on three small likelihood subsets
These are smoke tests, not leaderboard claims. Stage C is still an early graph-native language model prototype, not a production LLM.
The previous v0.1.0-prototype release is now considered the legacy small prototype checkpoint.