The Android assistant reads visible conversations through accessibility and local OCR, displaying analysis and reply suggestions in an overlay. Jev judges intent and response choices; a generative model drafts three candidates and Jev ranks them.
ggmlc: A multi-framework neural network compiler lowering PyTorch
monatis/ggmlc
VerifiedJev applicationDocumented
ggmlc: A multi-framework neural network compiler lowering PyTorch, JAX, Flax, and Keras models to portable, high-performance GGML execution. See Jev references and source code.
Repository description: A multi-framework neural network compiler lowering PyTorch, JAX, Flax, and Keras models to portable, high-performance GGML execution
What you can build with it
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Clone the repository and follow its README for install and usage. JevHunt has not run this project.
git clone https://github.com/monatis/ggmlc.gitProject facts
- Relationship to Jev
- Jev application
- Evidence
- Documented
- Language
- Python
- License
- Not reported; check the repository
- Origin
- Original repository
- Repository status
- Not archived
- Created
- 2026-08-22
- Last code update
- 2026-09-28
- GitHub stars
- 65
- Evidence checked
- Sep 29, 2026
- Metadata checked
- Sep 29, 2026
- Check status
- Up to date
Stars measure the whole repository, including work unrelated to Jev.
Evidence and scope
Documented records the linked documentation or source. JevHunt has not independently run or benchmarked this project.
**Sep 20, 2026 — ggmlc can Laya.** Compile [Laya], the open-source alternative to TypeSafe Jev, into a standalone C++ System 1 engine: typed `choice` / `score` / `noul` questions scored in one encoder pass — no generated tokens. English ModernBERT-large, mmBERT multilingual, and the typed-decisions specialist ship as F16 / Q8_0 / UD_Q4_K_M GGUFs. On an RTX 4050 Laptop, **~25 ms** per decision and **~143 ms** for a 7-question email preset. Details, CLI, and downloads: [`examples/laya`].
Evidence commit: 1519ea422ac31fb2e3e26947f69a0eb09217fbce
Discovered through: github-search.
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