RF
rasbt/reasoning-from-scratch
Implement a reasoning LLM in PyTorch from scratch, step by step
4.0k 575 +7/wk
GitHub
ai artificial-intelligence deep-learning deep-neural-networks large-language-models llms machine-learning python pytorch reasoning reinforcement-learning
Trend
3
Star & Fork Trend (44 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
rasbt/reasoning-from-scratch has +7 stars this period . 7-day velocity: 0.7%.
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| Metric | reasoning-from-scratch | helix-db | 3D-ResNets-PyTorch | pytorch-summary |
|---|---|---|---|---|
| Stars | 4.0k | 4.1k | 4.0k | 4.1k |
| Forks | 575 | 212 | 935 | 409 |
| Weekly Growth | +7 | +2 | +0 | -2 |
| Language | Jupyter Notebook | Rust | Python | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | Apache-2.0 | AGPL-3.0 | MIT | MIT |
Capability Radar vs helix-db
reasoning-from-scratch
helix-db
Maintenance Activity 100
Last code push 1 days ago.
Community Engagement 71
Fork-to-star ratio: 14.2%. Active community forking and contributing.
Issue Burden 70
Issue data not yet available.
Growth Momentum 50
+7 stars this period — 0.17% growth rate.
License Clarity 95
Licensed under Apache-2.0. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.