Instructions to use bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF", filename="DeepSeek-R1-Distill-Qwen-32B-IQ2_M.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF: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 bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF: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 bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF:Q4_K_M
- Ollama
How to use bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF with Ollama:
ollama run hf.co/bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF:Q4_K_M
- Unsloth Studio new
How to use bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF to start chatting
- Docker Model Runner
How to use bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF with Docker Model Runner:
docker model run hf.co/bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF:Q4_K_M
- Lemonade
How to use bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull bartowski/DeepSeek-R1-Distill-Qwen-32B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.DeepSeek-R1-Distill-Qwen-32B-GGUF-Q4_K_M
List all available models
lemonade list
Prompt format
Hi! I would like to confirm that prompt format is:
<|begin▁of▁sentence|>{system_prompt}<|User|>{prompt}<|Assistant|><|end▁of▁sentence|><|Assistant|>
and not:
<|begin▁of▁sentence|>{system_prompt}<|User|>{prompt}<|Assistant|><|end▁of▁sentence|><|User|>
Thank you ! :)
Have you manage to make them think? Mine can't and it just provide me with answer just like normal model unless i stated step by step like usual. I want to make it think inside <> or anything.
I'm waiting until llama-cpp-python works on this. In general, to push reasoning, I use a system prompt like this:
You are a friendly AI assistant. Reason through the query, then reflect on your reasoning, and finally provide your response.
You can replace the "You are a friendly AI assistant." part with whatever personality traits you want :)
Yes, that is what i did too, i stated them not to provide me the answer unless they finish their reasoning. Guess we really have to wait for updates. Thanks for answering :)
Ah no looks like the prompt extraction went weird for my page
what you see on my page is what i rendered, not what is saved in the template itself if you can use that instead
I'll update the pages though
Ok, thank you! Also thank you for your quants :)
Have you manage to make them think? Mine can't and it just provide me with answer just like normal model unless i stated step by step like usual. I want to make it think inside <> or anything.
The model does the thinking only if using the proper instruct format. If you wrote the format yourself make sure to be using the "|" and "▁" characters, which are different from "|" and "_"
When done correctly, it should output something like that:
[think]
The user wants to [do something]
bunch of steps
[/think]
Actual answer
Expect some (bad) front-ends to "eat" the 'think' tags (and sometimes, everything between the two) because people can't code properly anymore apparently.