Instructions to use tiny-random/phi-4-multimodal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tiny-random/phi-4-multimodal with Transformers:

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

pipe = pipeline("text-generation", model="tiny-random/phi-4-multimodal", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("tiny-random/phi-4-multimodal", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use tiny-random/phi-4-multimodal with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/tiny-random/phi-4-multimodal

SGLang

How to use tiny-random/phi-4-multimodal 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 "tiny-random/phi-4-multimodal" \
    --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": "tiny-random/phi-4-multimodal",
		"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 "tiny-random/phi-4-multimodal" \
        --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": "tiny-random/phi-4-multimodal",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use tiny-random/phi-4-multimodal with Docker Model Runner:
```
docker model run hf.co/tiny-random/phi-4-multimodal
```

yujiepan commited on Feb 28, 2025

Commit

8e1126d

verified ·

1 Parent(s): ca89336

Upload folder using huggingface_hub

Browse files

Files changed (2) hide show

README.md +2 -2
config.json +1 -1

README.md CHANGED Viewed

@@ -25,7 +25,7 @@ from PIL import Image
 from transformers import AutoModelForCausalLM, AutoProcessor, GenerationConfig
 # Define model path
-model_id = "yujiepan/phi-4-multimodal-tiny-random"
 # Load model and processor
 processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
@@ -114,7 +114,7 @@ from transformers import (
 )
 source_model_id = "microsoft/Phi-4-multimodal-instruct"
-save_folder = "/tmp/yujiepan/phi-4-multimodal-tiny-random"
 Path(save_folder).mkdir(exist_ok=True)
 AutoTokenizer.from_pretrained(source_model_id).save_pretrained(save_folder)

 from transformers import AutoModelForCausalLM, AutoProcessor, GenerationConfig
 # Define model path
+model_id = "tiny-random/phi-4-multimodal"
 # Load model and processor
 processor = AutoProcessor.from_pretrained(model_id, trust_remote_code=True)
 )
 source_model_id = "microsoft/Phi-4-multimodal-instruct"
+save_folder = "/tmp/tiny-random/phi-4-multimodal"
 Path(save_folder).mkdir(exist_ok=True)
 AutoTokenizer.from_pretrained(source_model_id).save_pretrained(save_folder)

config.json CHANGED Viewed

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "./tmp/yujiepan/phi-4-multimodal-tiny-random",
   "architectures": [
     "Phi4MMForCausalLM"
   ],

 {
+  "_name_or_path": "./tmp/tiny-random/phi-4-multimodal",
   "architectures": [
     "Phi4MMForCausalLM"
   ],