Instructions to use microsoft/Phi-4-mini-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use microsoft/Phi-4-mini-instruct with Transformers:

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

pipe = pipeline("text-generation", model="microsoft/Phi-4-mini-instruct", 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("microsoft/Phi-4-mini-instruct", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-4-mini-instruct", trust_remote_code=True)
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=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Inference
Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use microsoft/Phi-4-mini-instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "microsoft/Phi-4-mini-instruct"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "microsoft/Phi-4-mini-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/microsoft/Phi-4-mini-instruct

SGLang

How to use microsoft/Phi-4-mini-instruct 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 "microsoft/Phi-4-mini-instruct" \
    --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": "microsoft/Phi-4-mini-instruct",
		"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 "microsoft/Phi-4-mini-instruct" \
        --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": "microsoft/Phi-4-mini-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use microsoft/Phi-4-mini-instruct with Docker Model Runner:
```
docker model run hf.co/microsoft/Phi-4-mini-instruct
```

nguyenbh

ngxson HF Staff commited on Feb 28, 2025

Commit

f7a0a61

verified ·

1 Parent(s): f984c15

Fix "Norway problem" in YAML (#7)

Browse files

- Fix "Norway problem" in YAML (2b18b5b9361a36613005793b32f999d206be787b)

Co-authored-by: Xuan-Son Nguyen <ngxson@users.noreply.huggingface.co>

Files changed (1) hide show

README.md +24 -24

README.md CHANGED Viewed

@@ -2,30 +2,30 @@
 license: mit
 license_link: https://huggingface.co/microsoft/Phi-4-mini-instruct/resolve/main/LICENSE
 language:
-- multilingual
-- ar
-- zh
-- cs
-- da
-- nl
-- en
-- fi
-- fr
-- de
-- he
-- hu
-- it
-- ja
-- ko
-- no
-- pl
-- pt
-- ru
-- es
-- sv
-- th
-- tr
-- uk
 pipeline_tag: text-generation
 tags:
 - nlp

 license: mit
 license_link: https://huggingface.co/microsoft/Phi-4-mini-instruct/resolve/main/LICENSE
 language:
+- "multilingual"
+- "ar"
+- "zh"
+- "cs"
+- "da"
+- "nl"
+- "en"
+- "fi"
+- "fr"
+- "de"
+- "he"
+- "hu"
+- "it"
+- "ja"
+- "ko"
+- "no"
+- "pl"
+- "pt"
+- "ru"
+- "es"
+- "sv"
+- "th"
+- "tr"
+- "uk"
 pipeline_tag: text-generation
 tags:
 - nlp