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

Libraries

How to use microsoft/Phi-3-mini-128k-instruct-onnx 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-onnx", 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-onnx", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-128k-instruct-onnx", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

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

Use Docker

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

SGLang

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

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

eos_token_id error

by rajmethun0 - opened Apr 29, 2024

Discussion

rajmethun0

Apr 29, 2024

•

edited Apr 29, 2024

Hey guys, I tried running the onnx model using this code "import os
import onnxruntime_genai as og

model_path = os.path.abspath("./models/phi2")

model = og.Model(model_path)

tokenizer = og.Tokenizer(model)

prompt = '''def print_prime(n):
"""
Print all primes between 1 and n
"""'''

tokens = tokenizer.encode(prompt)

params = og.GeneratorParams(model)
params.set_search_options({"max_length":200})
####### Add the following line to enable cuda graph by passing the maximum batch size.
####### params.try_use_cuda_graph_with_max_batch_size(16)
params.input_ids = tokens

output_tokens = model.generate(params)

text = tokenizer.decode(output_tokens)

print("Output:")
print(text)" Not sure why I'm getting this error can someone help with this?"Phi-3-mini-128k-instruct-onnx\cpu_and_mobile\cpu-int4-rtn-block-32\genai_config.json' JSON Error: Unknown value: eos_token_id at line 29 index 27"

kvaishnavi

Microsoft org Apr 29, 2024

The EOS token id error has been fixed here. Can you uninstall ONNX Runtime GenAI (pip uninstall -y onnxruntime-genai onnxruntime-genai-cuda onnxruntime-genai-directml) and reinstall the latest version in the README instructions?

parinitarahi changed discussion status to closed May 1, 2024

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