Instructions to use microsoft/Phi-3-mini-128k-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use microsoft/Phi-3-mini-128k-instruct with Transformers:

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

pipe = pipeline("text-generation", model="microsoft/Phi-3-mini-128k-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-3-mini-128k-instruct", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-128k-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]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use microsoft/Phi-3-mini-128k-instruct with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "microsoft/Phi-3-mini-128k-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-3-mini-128k-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/microsoft/Phi-3-mini-128k-instruct

SGLang

How to use microsoft/Phi-3-mini-128k-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-3-mini-128k-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-3-mini-128k-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-3-mini-128k-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-3-mini-128k-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use microsoft/Phi-3-mini-128k-instruct with Docker Model Runner:
```
docker model run hf.co/microsoft/Phi-3-mini-128k-instruct
```

Fix `eos_token_id`

#39

by mrm8488 - opened Apr 25, 2024

base: refs/heads/main

←

from: refs/pr/39

Discussion Files changed

-1

mrm8488

Apr 25, 2024

It seems eos_token_id is <|end|> (32007) instead of <|endoftext|> (32000).
Context: https://twitter.com/altryne/status/1783567596467491109?t=k5HHVmTCGDt4-TkXF8KyNw&s=19

Fix `eos_token_id`9f082750

gugarosa

Microsoft org Apr 26, 2024

Please ensure that you are using the configuration defined in generation_config.json.

gugarosa changed pull request status to closed Apr 26, 2024

Wladastic

Apr 26, 2024

That config is pretty lazy though.
You made 3 token_ids being the potential eos_token now?

uestclx

Sep 9, 2024

Hi @gugarosa , the <|endoftext|> token is only functional for base model's training, and <|end|> is supposed to be the EOS token for instruction model and for multi-turn conversation.
Please also refer to:
https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct/commit/4d6c61da057c45bfc4dc4d3bfa5a691ecb9ce0cf
https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct/commit/a8977699a3d0820e80129fb3c93c20fbd9972c41

generation_config.json is indeed a lazy move. Adding a token that will never be generated into "eos_token_id" is just not the correct way.
Please reconsider changing "eos_token_id" to "<|end|>. Thanks!

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