Instructions to use meshllm/DeepSeek-R1-Q4_K_M-layers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use meshllm/DeepSeek-R1-Q4_K_M-layers with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf meshllm/DeepSeek-R1-Q4_K_M-layers
# Run inference directly in the terminal:
llama cli -hf meshllm/DeepSeek-R1-Q4_K_M-layers

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf meshllm/DeepSeek-R1-Q4_K_M-layers
# Run inference directly in the terminal:
llama cli -hf meshllm/DeepSeek-R1-Q4_K_M-layers

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 meshllm/DeepSeek-R1-Q4_K_M-layers
# Run inference directly in the terminal:
./llama-cli -hf meshllm/DeepSeek-R1-Q4_K_M-layers

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 meshllm/DeepSeek-R1-Q4_K_M-layers
# Run inference directly in the terminal:
./build/bin/llama-cli -hf meshllm/DeepSeek-R1-Q4_K_M-layers

Use Docker

docker model run hf.co/meshllm/DeepSeek-R1-Q4_K_M-layers

LM Studio
Jan

vLLM

How to use meshllm/DeepSeek-R1-Q4_K_M-layers with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "meshllm/DeepSeek-R1-Q4_K_M-layers"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "meshllm/DeepSeek-R1-Q4_K_M-layers",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/meshllm/DeepSeek-R1-Q4_K_M-layers

Ollama
How to use meshllm/DeepSeek-R1-Q4_K_M-layers with Ollama:
```
ollama run hf.co/meshllm/DeepSeek-R1-Q4_K_M-layers
```
Unsloth Desktop
Docker Model Runner
How to use meshllm/DeepSeek-R1-Q4_K_M-layers with Docker Model Runner:
```
docker model run hf.co/meshllm/DeepSeek-R1-Q4_K_M-layers
```

Lemonade

How to use meshllm/DeepSeek-R1-Q4_K_M-layers with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull meshllm/DeepSeek-R1-Q4_K_M-layers

Run and chat with the model

lemonade run user.DeepSeek-R1-Q4_K_M-layers-{{QUANT_TAG}}

List all available models

lemonade list

Atomic Chat

DeepSeek-R1-Q4_K_M-layers / automation /queue.json

jamesdumay

Queue layer package for unsloth/DeepSeek-R1-GGUF:DeepSeek-R1-Q4_K_M

abacfa1 verified 4 months ago

Raw

History Blame

494 Bytes

	{
	"schema_version": 1,
	"queued_at": "2026-05-08T21:33:13.323775276+00:00",
	"source_repo": "unsloth/DeepSeek-R1-GGUF",
	"source_file": "DeepSeek-R1-Q4_K_M/DeepSeek-R1-Q4_K_M-00001-of-00009.gguf",
	"quant": "Q4_K_M",
	"target_repo": "meshllm/DeepSeek-R1-Q4_K_M-layers",
	"model_id": "unsloth/DeepSeek-R1-GGUF:DeepSeek-R1-Q4_K_M",
	"mesh_llm_ref": "main",
	"github_run_url": "https://github.com/Mesh-LLM/mesh-llm/actions/runs/25580536970",
	"recent_rank": null,
	"popular_rank": 36
	}