Instructions to use ubergarm/DeepSeek-R1-0528-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use ubergarm/DeepSeek-R1-0528-GGUF 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 ubergarm/DeepSeek-R1-0528-GGUF:IQ1_S
# Run inference directly in the terminal:
llama cli -hf ubergarm/DeepSeek-R1-0528-GGUF:IQ1_S

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf ubergarm/DeepSeek-R1-0528-GGUF:IQ1_S
# Run inference directly in the terminal:
llama cli -hf ubergarm/DeepSeek-R1-0528-GGUF:IQ1_S

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 ubergarm/DeepSeek-R1-0528-GGUF:IQ1_S
# Run inference directly in the terminal:
./llama-cli -hf ubergarm/DeepSeek-R1-0528-GGUF:IQ1_S

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 ubergarm/DeepSeek-R1-0528-GGUF:IQ1_S
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ubergarm/DeepSeek-R1-0528-GGUF:IQ1_S

Use Docker

docker model run hf.co/ubergarm/DeepSeek-R1-0528-GGUF:IQ1_S

LM Studio
Jan

vLLM

How to use ubergarm/DeepSeek-R1-0528-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ubergarm/DeepSeek-R1-0528-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": "ubergarm/DeepSeek-R1-0528-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ubergarm/DeepSeek-R1-0528-GGUF:IQ1_S

Ollama
How to use ubergarm/DeepSeek-R1-0528-GGUF with Ollama:
```
ollama run hf.co/ubergarm/DeepSeek-R1-0528-GGUF:IQ1_S
```

Unsloth Studio

How to use ubergarm/DeepSeek-R1-0528-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 ubergarm/DeepSeek-R1-0528-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 ubergarm/DeepSeek-R1-0528-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for ubergarm/DeepSeek-R1-0528-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use ubergarm/DeepSeek-R1-0528-GGUF with Docker Model Runner:
```
docker model run hf.co/ubergarm/DeepSeek-R1-0528-GGUF:IQ1_S
```

Lemonade

How to use ubergarm/DeepSeek-R1-0528-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull ubergarm/DeepSeek-R1-0528-GGUF:IQ1_S

Run and chat with the model

lemonade run user.DeepSeek-R1-0528-GGUF-IQ1_S

List all available models

lemonade list

S1 Base 671B fine tune ik llama GGUF request?

#18

by facedwithahug - opened Aug 10, 2025

Discussion

facedwithahug

Aug 10, 2025

Hi Ubergarm,

Thanks again for your persistence in getting these quantized models out there!

I have been looking into the S1 Base 671B model, a fine tune of deepseek V3/R1, and wanted to know if you would have bandwidth to quantize it. I will try to quantize it myself, but I haven't really gone through the motions of quantizing this large of a model before and what it might take in terms of hardware/blood/sweat and tears. Anyway, apologies for the deepseek R1 only fans here but, S1 base in principle may be very good.

ubergarm

Owner Aug 10, 2025

Oh hey I think someone requested me do this model on r/LocalLLaMA but when I went to reply to them it didn't show me the comment anymore which was really strange..

I believe you're talking about that model fine-tuned on scientific papers? Specifically this one?

https://huggingface.co/ScienceOne-AI/S1-Base-671B

Not sure I have the bandwidth to do a full set of those, but possibly a single one or something for whatever size would be good for people? But if you want it faster I suggest you create imatrix and quantize it yourself and upload to HF and tag it with ik_llama.cpp so folks can find it. Feel free to re-use my recipes or check out @Thireus work for recipe combinations as well.

I have a quant cookers basic guide here: https://github.com/ikawrakow/ik_llama.cpp/discussions/434 however it doesn't cover the fp8 safetensors to bf16 GGUF process which is described here: https://github.com/ikawrakow/ik_llama.cpp/discussions/434

Keep us posted if you make any progress or holler at me if u get stuck!

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