Instructions to use microsoft/Phi-3-mini-4k-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use microsoft/Phi-3-mini-4k-instruct with Transformers:

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

pipe = pipeline("text-generation", model="microsoft/Phi-3-mini-4k-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-4k-instruct", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-4k-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-3-mini-4k-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-4k-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-4k-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/microsoft/Phi-3-mini-4k-instruct

SGLang

How to use microsoft/Phi-3-mini-4k-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-4k-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-4k-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-4k-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-4k-instruct",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use microsoft/Phi-3-mini-4k-instruct with Docker Model Runner:
```
docker model run hf.co/microsoft/Phi-3-mini-4k-instruct
```

the phi3 model not learning from training data using orpo.

#44

by Imran1 - opened Apr 27, 2024

Discussion

Imran1

Apr 27, 2024

i train the model using ORPO trainer but the model not learn the training data.
should i need to run it for more epoch?

gugarosa

Microsoft org May 1, 2024

Could you please post more information about your training?

Imran1

May 2, 2024

@gugarosa
The dataset size is, 25k sample.
Having instructions, question, reject and chosen.
Try with both learning 1e-6 and 8e-6 as in the paper suggest with 3 and 5 epochs.
After that when I ask that domain related questions, so the model fail to answer some time repeat the answer.
However the model perform well in other questions which not related to that domain.

NickyNicky

May 5, 2024

•

edited May 5, 2024

The model does not learn well because they destroyed it by deleting the tokens they had.

I trained him here and I see that he is destroyed, for me.

https://huggingface.co/NickyNicky/Phi-3-mini-4k-instruct_orpo_V2

add these new tokens to see but I don't really like it:
https://huggingface.co/NickyNicky/Phi-3-mini-4k-instruct_orpo_V2/blob/main/added_tokens.json
https://huggingface.co/NickyNicky/Phi-3-mini-4k-instruct_orpo_V2/blob/main/tokenizer_config.json

I managed to download some files and leave it almost as it was but for me it is destroyed.

add new 120k dataset function_call :
https://huggingface.co/datasets/NickyNicky/oasst2_orpo_mix_function_call_phi_3_v1

tokens deleted:

"32011": {
"content": "<|function_list|>",
"lstrip": false,
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"single_word": false,
"special": true
},
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"rstrip": true,
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"special": true
},
"32013": {
"content": "<|code|>",
"lstrip": false,
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"special": true
},
"32014": {
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"lstrip": false,
"normalized": false,
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"single_word": false,
"special": true
},
"32015": {
"content": "<|summary|>",
"lstrip": false,
"normalized": false,
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"special": true
},
"32016": {
"content": "<|resource|>",
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},
"32017": {
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},
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"32031": {
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"32032": {
"content": "<|data|>",
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},
"32033": {
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},
"32034": {
"content": "<|sys|>",
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"32035": {
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"32036": {
"content": "<|inst|>",
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"32037": {
"content": "<|/inst|>",
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}
},
"additional_special_tokens": [
"<|/inst|>"
],

nguyenbh changed discussion status to closed Jul 1, 2024

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