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

Libraries

How to use unsloth/DeepSeek-R1-0528-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="unsloth/DeepSeek-R1-0528-GGUF", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("unsloth/DeepSeek-R1-0528-GGUF", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("unsloth/DeepSeek-R1-0528-GGUF", trust_remote_code=True)

llama-cpp-python

How to use unsloth/DeepSeek-R1-0528-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="unsloth/DeepSeek-R1-0528-GGUF",
	filename="BF16/DeepSeek-R1-0528-BF16-00001-of-00030.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use unsloth/DeepSeek-R1-0528-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
llama-cli -hf unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
llama-cli -hf unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL

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 unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
./llama-cli -hf unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL

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 unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL
# Run inference directly in the terminal:
./build/bin/llama-cli -hf unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL

Use Docker

docker model run hf.co/unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL

LM Studio
Jan

vLLM

How to use unsloth/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 "unsloth/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": "unsloth/DeepSeek-R1-0528-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL

SGLang

How to use unsloth/DeepSeek-R1-0528-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "unsloth/DeepSeek-R1-0528-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "unsloth/DeepSeek-R1-0528-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "unsloth/DeepSeek-R1-0528-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "unsloth/DeepSeek-R1-0528-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Ollama
How to use unsloth/DeepSeek-R1-0528-GGUF with Ollama:
```
ollama run hf.co/unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL
```

Unsloth Studio

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

How to use unsloth/DeepSeek-R1-0528-GGUF with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use unsloth/DeepSeek-R1-0528-GGUF with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL

Run Hermes

hermes

Docker Model Runner
How to use unsloth/DeepSeek-R1-0528-GGUF with Docker Model Runner:
```
docker model run hf.co/unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL
```

Lemonade

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

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull unsloth/DeepSeek-R1-0528-GGUF:UD-Q4_K_XL

Run and chat with the model

lemonade run user.DeepSeek-R1-0528-GGUF-UD-Q4_K_XL

List all available models

lemonade list

Update - Tool Calling + Chat Template bug fixes

#20

pinned

by danielhanchen - opened Jun 11, 2025

Discussion

danielhanchen

Unsloth AI org Jun 11, 2025

Just updated DeepSeek-R1-0528 GGUFs and BF16 safetensors (the big 671B model)

Native tool calling is now supported. Uses https://github.com/sgl-project/sglang/pull/6765 and https://github.com/vllm-project/vllm/pull/18874 which shows DeepSeek-R1 getting 93.25% on the BFCL** Berkeley Function-Calling Leaderboard https://gorilla.cs.berkeley.edu/leaderboard.html.
Use it via --jinja in llama.cpp. Native transformers and vLLM should work as well.
Had to fix multiple issues in SGLang and vLLM's PRs (dangling newlines etc)
Chat template bug fixes add_generation_prompt now works - previously <|Assistant|> was auto appended - now it's toggle-able. Fixes many issues, and should streamline chat sessions.
UTF-8 encoding of tokenizer_config.json is now fixed - now works in Windows.
Ollama is now fixed on using more memory - I removed num_ctx and num_predict -> it'll now default to Ollama's defaults. This allocated more KV cache VRAM, thus spiking VRAM usage. Please update your context length manually.
[10th June 2025] Update - LM Studio now also works
Ollama works by using the TQ1_0 quant!

ollama run hf.co/unsloth/DeepSeek-R1-0528-GGUF:TQ1_0

Please re-download all weights to get the latest updates!

danielhanchen pinned discussion Jun 11, 2025

Rotating

Jun 11, 2025

•

edited Jun 11, 2025

What is 3. about? I think I can ignore all the other ones and not re-download.

ciprianv

Jun 14, 2025

Why UD-Q2_XL was deleted? Is UD-IQ2_M better?

shimmyshimmer

Unsloth AI org Jun 15, 2025

What is 3. about? I think I can ignore all the other ones and not re-download.

It's not that important

Why UD-Q2_XL was deleted? Is UD-IQ2_M better?

Oh crap you're right, it was never supposed to be deleted lol thanks for the warning

danielhanchen

Unsloth AI org Jun 15, 2025

I also noticed Q8_0 was gone!! I'll redo Q8_0 and Q2_K_XL

danielhanchen

Unsloth AI org Jun 15, 2025

@ciprianv Q2_K_XL and Q8_0 are back - unsure why it got removed sorry!

ciprianv

Jun 15, 2025

Thank you!

nulled

Jun 16, 2025

Why is DeepSeek-R1-0528-UD-IQ2_M-00001-of-00005.gguf much newer than the rest of its parts? Are all the files updated (as mentioned above, or just the first one?

jschober

Jun 20, 2025

Hello.

I am trying to run this on a machine with Mi300X AMD GPU (if that matters), but I get weird too calling issues

./build/bin/llama-server -hf unsloth/DeepSeek-R1-0528-GGUF:TQ1_0 --cache-type-k q4_0 --threads -1 --n-gpu-layers 99 --prio 3 --temp 0.6 --top_p 0.95 --min_p 0.01 --ctx-size 16384 --seed 3407 -ot ".ffn_.*_exps.=CPU" --jinja

When the LLM attempts to call a tool, it throws

Using host libthread_db library "/lib/x86_64-linux-gnu/libthread_db.so.1".
0x00007423997107e3 in __GI___wait4 (pid=33102, stat_loc=0x0, options=0, usage=0x0) at ../sysdeps/unix/sysv/linux/wait4.c:30
warning: 30	../sysdeps/unix/sysv/linux/wait4.c: No such file or directory
#0  0x00007423997107e3 in __GI___wait4 (pid=33102, stat_loc=0x0, options=0, usage=0x0) at ../sysdeps/unix/sysv/linux/wait4.c:30
30	in ../sysdeps/unix/sysv/linux/wait4.c
#1  0x000074239b74b196 in ggml_print_backtrace () from /root/llama.cpp/build/bin/libggml-base.so
#2  0x000074239b75d9a6 in ggml_uncaught_exception() () from /root/llama.cpp/build/bin/libggml-base.so
#3  0x0000742399abb0da in ?? () from /lib/x86_64-linux-gnu/libstdc++.so.6
#4  0x0000742399aa5a55 in std::terminate() () from /lib/x86_64-linux-gnu/libstdc++.so.6
#5  0x0000742399abb391 in __cxa_throw () from /lib/x86_64-linux-gnu/libstdc++.so.6
#6  0x00000000003d2d3b in common_chat_msg_diff::compute_diffs(common_chat_msg const&, common_chat_msg const&) ()
#7  0x00000000003508b9 in server_slot::update_chat_msg(std::vector<common_chat_msg_diff, std::allocator<common_chat_msg_diff> >&) ()
#8  0x000000000034e26d in server_context::send_final_response(server_slot&) ()
#9  0x000000000034c97d in server_context::update_slots() ()
#10 0x00000000002cc464 in server_queue::start_loop() ()
#11 0x0000000000288a5f in main ()
[Inferior 1 (process 33044) detached]
terminate called after throwing an instance of 'std::runtime_error'
  what():  Invalid diff: now finding less tool calls!
Aborted (core dumped)

jschober

Jun 26, 2025

Seem this same issue on a different (nvidia) machine, and V3-0528. Is there a way to get these models to perform tool calls with llama.cpp correctly?

Template supports tool calls but does not natively describe tools. The fallback behaviour used may produce bad results, inspect prompt w/ --verbose & consider overriding the template.
srv  params_from_: Chat format: DeepSeek R1
....
/home/ubuntu/llama.cpp/build/bin/libggml-base.so(+0x158fb)[0x7f51338028fb]
/home/ubuntu/llama.cpp/build/bin/libggml-base.so(ggml_print_backtrace+0x21c)[0x7f5133802d5c]
/home/ubuntu/llama.cpp/build/bin/libggml-base.so(+0x24bff)[0x7f5133811bff]
/lib/x86_64-linux-gnu/libstdc++.so.6(+0xbb0da)[0x7f51334bb0da]
/lib/x86_64-linux-gnu/libstdc++.so.6(_ZSt10unexpectedv+0x0)[0x7f51334a5a55]
/lib/x86_64-linux-gnu/libstdc++.so.6(+0xbb391)[0x7f51334bb391]
./llama-server(+0x33bcc)[0x62c8fd587bcc]
./llama-server(+0xa596b)[0x62c8fd5f996b]
./llama-server(+0xa79c1)[0x62c8fd5fb9c1]
./llama-server(+0xc014f)[0x62c8fd61414f]
./llama-server(+0x858b5)[0x62c8fd5d98b5]
./llama-server(+0x4e103)[0x62c8fd5a2103]
/lib/x86_64-linux-gnu/libc.so.6(+0x2a1ca)[0x7f513302a1ca]
/lib/x86_64-linux-gnu/libc.so.6(__libc_start_main+0x8b)[0x7f513302a28b]
./llama-server(+0x500f5)[0x62c8fd5a40f5]
terminate called after throwing an instance of 'std::runtime_error'
  what():  Invalid diff: now finding less tool calls!
Aborted (core dumped)

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