authentrics/nemotron-training-dynamics
  
Diagnosing What Changed Across a Model's Training Run
Tracking parameter and activation drift across the NVIDIA Nemotron Cascade 8B checkpoint lineage to see what changed, where, and when during training.
Authentrics is a high-performance neural-network analysis library (Python wheel over a C++ core). It audits and maintains model checkpoints: parameter/behavioral drift, compliant data removal without full retraining, and loss-driven optimization without backprop. Analysis runs locally on your machine — only project metadata (names, descriptions) is exchanged with Authentrics servers, never your model weights.
What this demo shows
- `static_analysis` — audit parameter drift between pairs of sequential checkpoints.
- `activation_analysis` — catch behavioral drift in intermediate activations.
Reproduce this analysis
The public code and outputs behind this demo live in https://github.com/Authentrics-ai/authentrics-model-analysis-experiments:
src/analysis/nemotron_cascade_static.pysrc/analysis/nemotron_cascade_dynamic.pysrc/analysis/render_nemotron_dashboard.pyOutputs (JSON + Plotly HTML dashboards) are published underoutput/nemotron_cascade/.
Weights: Training-dynamics walkthrough on the NVIDIA Nemotron Cascade 8B checkpoints; no derived weights are published. Reproduce the analysis locally with the SDK below.
Reproduce it yourself
pip install authentrics # Linux x86_64, Python 3.11–3.13
authrx init # paste API key (stored at ~/.local/state/authentrics/api_key)
# or, for CI / non-interactive:
export AUTHRX_API_KEY=<your_api_key>Generate an API key and read the full docs at https://app.authentrics.ai/.
Produced with the [Authentrics SDK](https://app.authentrics.ai/) v0.35.1 — checkpoint analysis that runs locally on your own hardware; only project metadata ever leaves your machine, never your weights.
Links
- App & API keys: https://app.authentrics.ai/
- Docs & API reference: https://app.authentrics.ai/docs
- Examples & user guide: https://github.com/Authentrics-ai/authentrics-analysis-examples
- Contact: info@authentrics.ai
