中文Sign up

mys/kev-4b-GGUF

🤗 Hugging Face sourceapache-2.04B activated17 GBGGUF✓ 3 checksumsupdated today
Submit in one command

Run it next to your model folder. It makes the torrent, checks your files against Hugging Face, and submits it. You just start seeding and paste your key from your account. It only reads your files and never changes them. Read the script first if you like.

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo mys/kev-4b-GGUF ./model-folder
Needs a seeder →

Kev 4B GGUF (ggmlc)

English System 1 decision model compiled from jaredpalmer/kev-4b (Qwen3.5-4B hybrid Gated DeltaNet, LoRA merged in fp32 before export, context 2048).

These files are not llama.cpp / llama-cli GGUFs. They are produced by ggmlc. Loading them in llama.cpp will fail.

Typed questions (choice / score / noul) are scored in one forward. There is no autoregressive token generation. Tokenizer, sequence program, and postprocess live in the GGUF (ggmlc.decision).

Source and CLI: examples/laya

Smaller siblings: kev-0.5b-GGUF, kev-0.8b-GGUF

Files

File Quant Size Notes
kev_4b_f16.gguf F16 ~8.05 GB Best numerical match. Qwen3.5 zero-centered RMS is fused.
kev_4b_q8_0.gguf Q8_0 ~4.29 GB Uniform Q8_0. 1D norms stay F32.
kev_4b_ud_q4_k_m.gguf UD_Q4_K_M ~4.02 GB Embedding stays F16, sensitive projections Q8_0, other weights Q4_0. Smaller than uniform Q8_0. 
huggingface-cli download mys/kev-4b-GGUF kev_4b_q8_0.gguf --local-dir .

Run with laya

laya info kev_4b_q8_0.gguf
laya decide kev_4b_q8_0.gguf --preset email --device auto --cuda-graph
laya serve kev_4b_q8_0.gguf --port 8080 --device auto --cuda-graph
laya bench kev_4b_q8_0.gguf --preset email --device auto --cuda-graph

serve is Decision Studio plus POST /v1/systemone (TypeSafe). The advertised model id is kev-4b.

License

Apache 2.0, same as jaredpalmer/kev-4b. Compiler: ggmlc (MIT).