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

Libraries

How to use amgadhasan/phi-4 with Transformers:

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

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

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use amgadhasan/phi-4 with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/amgadhasan/phi-4

SGLang

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

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

amgadhasan commited on Dec 16, 2024

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@@ -1,5 +1,6 @@
 ---
 pipeline_tag: text-generation
 ---
 # Phi-4
 Note: This checkpoint is copied from [Azure AI Foundary](https://ai.azure.com/explore/models/Phi-4/version/1/registry/azureml?tid=1a57c1b4-f329-43bc-be9d-db002574ae97)
@@ -28,4 +29,4 @@ Multilingual data constitutes about 8% of our overall data. We are focusing on t
 |Property|Description|
 |---|---|
 |Supported data types|Inputs: text, Outputs: text|
-|Supported languages|en, ar, bn, cs, da, de, el, es, fa, fi, fr, gu, ha, he, hi, hu, id, it, ja, jv, kn, ko, ml, mr, nl, no, or, pa, pl, ps, pt, ro, ru, sv, sw, ta, te, th, tl, tr, uk, ur, vi, yo, zh|

 ---
 pipeline_tag: text-generation
+library_name: transformers
 ---
 # Phi-4
 Note: This checkpoint is copied from [Azure AI Foundary](https://ai.azure.com/explore/models/Phi-4/version/1/registry/azureml?tid=1a57c1b4-f329-43bc-be9d-db002574ae97)
 |Property|Description|
 |---|---|
 |Supported data types|Inputs: text, Outputs: text|
+|Supported languages|en, ar, bn, cs, da, de, el, es, fa, fi, fr, gu, ha, he, hi, hu, id, it, ja, jv, kn, ko, ml, mr, nl, no, or, pa, pl, ps, pt, ro, ru, sv, sw, ta, te, th, tl, tr, uk, ur, vi, yo, zh|