Instructions to use FastFlowLM/Deepseek-R1-Distill-Llama-8B-NPU2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FastFlowLM/Deepseek-R1-Distill-Llama-8B-NPU2 with Transformers:

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

pipe = pipeline("text-generation", model="FastFlowLM/Deepseek-R1-Distill-Llama-8B-NPU2")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("FastFlowLM/Deepseek-R1-Distill-Llama-8B-NPU2")
model = AutoModelForCausalLM.from_pretrained("FastFlowLM/Deepseek-R1-Distill-Llama-8B-NPU2", device_map="auto")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use FastFlowLM/Deepseek-R1-Distill-Llama-8B-NPU2 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FastFlowLM/Deepseek-R1-Distill-Llama-8B-NPU2"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FastFlowLM/Deepseek-R1-Distill-Llama-8B-NPU2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/FastFlowLM/Deepseek-R1-Distill-Llama-8B-NPU2

SGLang

How to use FastFlowLM/Deepseek-R1-Distill-Llama-8B-NPU2 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 "FastFlowLM/Deepseek-R1-Distill-Llama-8B-NPU2" \
    --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": "FastFlowLM/Deepseek-R1-Distill-Llama-8B-NPU2",
		"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 "FastFlowLM/Deepseek-R1-Distill-Llama-8B-NPU2" \
        --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": "FastFlowLM/Deepseek-R1-Distill-Llama-8B-NPU2",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use FastFlowLM/Deepseek-R1-Distill-Llama-8B-NPU2 with Docker Model Runner:
```
docker model run hf.co/FastFlowLM/Deepseek-R1-Distill-Llama-8B-NPU2
```

Deepseek-R1-Distill-Llama-8B-NPU2

Commit History

May 7

20:32
Fix chat_template crash when assistant message omits the `content` key⁠

qgallouedec HF Staff

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b808369

Aug 11, 2025

20:09
Update README.md

FastFlowLM

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deca786
20:08
Update README.md

FastFlowLM

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91dc357

Jul 31, 2025

20:17
Create README.md

FastFlowLM

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8deccd0

Jul 26, 2025

14:34
Update config.json

FastFlowLM

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1902964

Jul 25, 2025

19:21
update_mm

ngdxzy

59fffc3

Jul 16, 2025

20:04
update_glu

ngdxzy

d77ceb2

Jul 9, 2025

20:59
Upload tokenizer_config.json

FastFlowLM

Verified signature
16ac420

Jun 13, 2025

21:12
updateMM

ngdxzy

fb69208
18:48
support_prefill

ngdxzy

94e495f

May 23, 2025

18:36
add_bin

ngdxzy

cea47d5

May 15, 2025

16:22
addatt

ngdxzy

5770a06
16:17
init

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4ff9fbd

Commit History

May 7

Fix chat_template crash when assistant message omits the `content` key⁠

Aug 11, 2025

Update README.md

Update README.md

Jul 31, 2025

Create README.md

Jul 26, 2025

Update config.json

Jul 25, 2025

update_mm

Jul 16, 2025

update_glu

Jul 9, 2025

Upload tokenizer_config.json

Jun 13, 2025

updateMM

support_prefill

May 23, 2025

add_bin

May 15, 2025

addatt

init