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 DevQuasar/inclusionAI.Ling-plus-GGUF:
# Run inference directly in the terminal:
llama-cli -hf DevQuasar/inclusionAI.Ling-plus-GGUF:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf DevQuasar/inclusionAI.Ling-plus-GGUF:
# Run inference directly in the terminal:
llama-cli -hf DevQuasar/inclusionAI.Ling-plus-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 DevQuasar/inclusionAI.Ling-plus-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf DevQuasar/inclusionAI.Ling-plus-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 DevQuasar/inclusionAI.Ling-plus-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf DevQuasar/inclusionAI.Ling-plus-GGUF:
Use Docker
docker model run hf.co/DevQuasar/inclusionAI.Ling-plus-GGUF:
Quick Links

'Make knowledge free for everyone'

Quantized version of: inclusionAI/Ling-plus Buy Me a Coffee at ko-fi.com

Downloads last month
29
GGUF
Model size
293B params
Architecture
bailingmoe
Hardware compatibility
Log In to add your hardware

1-bit

2-bit

3-bit

4-bit

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

Model tree for DevQuasar/inclusionAI.Ling-plus-GGUF

Quantized
(1)
this model

Collections including DevQuasar/inclusionAI.Ling-plus-GGUF