Instructions to use cortexso/deepseek-r1-distill-llama-70b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use cortexso/deepseek-r1-distill-llama-70b 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 cortexso/deepseek-r1-distill-llama-70b:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf cortexso/deepseek-r1-distill-llama-70b:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf cortexso/deepseek-r1-distill-llama-70b:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf cortexso/deepseek-r1-distill-llama-70b:Q4_K_M

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 cortexso/deepseek-r1-distill-llama-70b:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf cortexso/deepseek-r1-distill-llama-70b:Q4_K_M

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 cortexso/deepseek-r1-distill-llama-70b:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf cortexso/deepseek-r1-distill-llama-70b:Q4_K_M

Use Docker

docker model run hf.co/cortexso/deepseek-r1-distill-llama-70b:Q4_K_M

LM Studio
Jan

vLLM

How to use cortexso/deepseek-r1-distill-llama-70b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cortexso/deepseek-r1-distill-llama-70b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cortexso/deepseek-r1-distill-llama-70b",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/cortexso/deepseek-r1-distill-llama-70b:Q4_K_M

Ollama
How to use cortexso/deepseek-r1-distill-llama-70b with Ollama:
```
ollama run hf.co/cortexso/deepseek-r1-distill-llama-70b:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use cortexso/deepseek-r1-distill-llama-70b with Docker Model Runner:
```
docker model run hf.co/cortexso/deepseek-r1-distill-llama-70b:Q4_K_M
```

Lemonade

How to use cortexso/deepseek-r1-distill-llama-70b with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull cortexso/deepseek-r1-distill-llama-70b:Q4_K_M

Run and chat with the model

lemonade run user.deepseek-r1-distill-llama-70b-Q4_K_M

List all available models

lemonade list

Atomic Chat

Overview

DeepSeek developed and released the DeepSeek R1 Distill Llama 70B model, a distilled version of the Llama 70B language model. This model represents the pinnacle of the DeepSeek R1 Distill series, designed for exceptional performance in text generation, dialogue tasks, and advanced reasoning, offering unparalleled capabilities for large-scale AI applications.

The model is ideal for enterprise-grade applications, research, conversational AI, and large-scale knowledge systems, providing top-tier accuracy, safety, and efficiency.

Variants

No	Variant	Cortex CLI command
1	Deepseek-r1-distill-llama-70b-70b	`cortex run deepseek-r1-distill-llama-70b:70b`

Use it with Jan (UI)

Install Jan using Quickstart
Use in Jan model Hub:
```
cortexso/deepseek-r1-distill-llama-70b
```

Use it with Cortex (CLI)

Install Cortex using Quickstart

Run the model with command:

cortex run deepseek-r1-distill-llama-70b

Credits

Author: DeepSeek
Converter: Homebrew
Original License: License
Papers: DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Downloads last month: 66

GGUF

Model size

71B params

Architecture

llama

Hardware compatibility

4-bit

Collection including cortexso/deepseek-r1-distill-llama-70b

DeepSeek-R1

Collection

6 items • Updated Jan 23, 2025