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Testing out System One Models
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CommunityJev Demos & Experiments
SystemOneModels
A Python study collection for System One models: notes on Jev and its API primitives, a comparison against Laya, Cerebellum-2B, Kev-0.5B, BERT and XGBoost, and working demos including a local Laya run and an OpenJev API demo.
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- Language
- Python
- Reading time
- 2 min
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- Author
- Lancer59
- Last verified
- Oct 2026
Works forJev for Classification
Used inJev for Software & DevTools
- Languages
- Python
- Capabilities
- Open sourceRuns locally
Highlights
- explanation.md is a deep dive into Jev: what it is, how RLCD works and the API primitives.
- comparison.md puts Jev against Laya, Cerebellum-2B, Kev-0.5B, BERT and XGBoost.
- demo_laya.py runs 6 support tickets through Laya English with 4 questions each; demo_openjev.py needs only an API key.
- Model weights are excluded from the repo (808 MB, gitignored); the README shows hf download convaiinnovations/laya --local-dir ./models/laya.
- Frames System One as fast, structured decisions for automation rather than chat, named after Kahneman's System 1; created 2026-09-20.
Quickstart
bash
pip install torch --index-url https://download.pytorch.org/whl/cpu
pip install laya transformers
hf download convaiinnovations/laya --local-dir ./models/layaWatch out
README reviewed 2026-10-17; the excerpt stops in the middle of the model-download cleanup step, so the rest of setup and the contents of the comparison document are not captured. No license is listed, and the repository had zero stars at sweep time.
Questions about this entry
Short answers drawn from the linked project or page.
A Python study repository for System One models: documentation on Jev, a model comparison and demo scripts. It describes System One models as making fast, structured decisions for automation rather than chat.
Six files: explanation.md on Jev and RLCD, comparison.md against six alternatives, demo_laya.py and demo_openjev.py as working demos, setup_laya.md for Laya, and Jev-SystemOne.md with notes on Jev and TypeSafe AI.
Install torch from the CPU wheel index plus laya and transformers, download the English checkpoint with hf download convaiinnovations/laya --local-dir ./models/laya, then run demo_laya.py, which processes six support tickets with four questions each.
Only for the OpenJev demo: demo_openjev.py needs no local model and just an API key, while the Laya demo runs the open-weights model locally. The captured excerpt does not list the key source or pricing.
About 808 MB. They are excluded from the repository via .gitignore and downloaded from Hugging Face instead, and the README also tells you to delete two unneeded subfolders to save roughly 1.4 GB.
The comparison document covers Jev versus Laya, Cerebellum-2B, Kev-0.5B, BERT and XGBoost, per the file table. The digest does not include the comparison's results or methodology.
No license is listed in the metadata; the Python repository was created and pushed on 2026-09-20 with zero stars at sweep time, so it reads as a personal study rather than a maintained product.
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