akhilaaa3/Jev-Omni
archivedmodel
Text classification model from akhilaaa3 (HF pipeline tag; the card has no one-line description). Dense, 12B params. Context: 256K tokens (config). License: apache-2.0.
- Org
- akhilaaa3
- Released
- 2026-09-20
- Status
- archived
- License
- apache-2.0 (permissive)
- Parameters
- 12.0B
- Architecture
- dense · Gemma4UnifiedForConditionalGeneration
- Context
- 262,144 tokens
- Task
- text-classification · text
- Signal
- 420 HF likes · 5453 downloads
- Archived
- 2026-10-20 (aged out (older than 30 days); stats as last seen)
Runs on
mixed: real files + estimate; need = weights + FP16 KV cache for 8K tokens + 1GB. A sizing calculation, not tested.
- Q4 ~11.6 GB: 16GB GPU (5060 Ti / 4060 Ti / 4080 / 5080), 16GB GPU (7800 XT / 9070 XT), Mac 16GB
- Q8 ~16.9 GB (estimated size): 24GB GPU (3090 / 4090), 24GB GPU (7900 XTX), Arc B60 24GB, Mac 24GB, Mac 36GB, CPU only, 32GB RAM (slow)
- FP16 ~28.1 GB: 32GB GPU (5090), 48GB GPU (RTX 6000 Ada / A6000), 96GB GPU (RTX Pro 6000 Blackwell), 1× DGX Spark (128GB), 2× DGX Spark (256GB), Strix Halo 128GB unified (~96GB usable), Arc B70 32GB, Mac 48GB, Mac 64GB (M1 Max), Mac 96GB, Mac 128GB, Mac 192GB, Mac 256GB, Mac 512GB, CPU only, 64GB RAM (slow), CPU only, 128GB RAM (slow), CPU only, 256GB RAM (slow)
Links
First published here 2026-09-20 · updated 2026-10-20 · markdown · JSON