How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf kai-os/Carnice-27b-GGUF:
# Run inference directly in the terminal:
llama-cli -hf kai-os/Carnice-27b-GGUF:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf kai-os/Carnice-27b-GGUF:
# Run inference directly in the terminal:
llama-cli -hf kai-os/Carnice-27b-GGUF:
Use pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf kai-os/Carnice-27b-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf kai-os/Carnice-27b-GGUF:
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf kai-os/Carnice-27b-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf kai-os/Carnice-27b-GGUF:
Use Docker
docker model run hf.co/kai-os/Carnice-27b-GGUF:
Quick Links

Carnice-27b Banner

Carnice-27b-GGUF

GGUF quantizations of the merged Carnice-27b full model for local inference.

Included quantizations:

  • Q4_K_M
  • Q6_K
  • Q8_0

Base merged model:

  • kai-os/Carnice-27b

These GGUF files were converted from the merged full-model release, not from the raw adapter.

Downloads last month
270
GGUF
Model size
27B params
Architecture
qwen35
Hardware compatibility
Log In to add your hardware

4-bit

6-bit

8-bit

Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 2 Ask for provider support

Model tree for kai-os/Carnice-27b-GGUF

Base model

Qwen/Qwen3.5-27B
Quantized
(5)
this model
Quantizations
1 model

Collection including kai-os/Carnice-27b-GGUF