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microsoft
/
phi-1_5

Text Generation
Transformers
Safetensors
English
phi
nlp
code
text-generation-inference
Model card Files Files and versions
xet
Community
94

Instructions to use microsoft/phi-1_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use microsoft/phi-1_5 with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-generation", model="microsoft/phi-1_5")
    # Load model directly
    from transformers import AutoTokenizer, AutoModelForCausalLM
    
    tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-1_5")
    model = AutoModelForCausalLM.from_pretrained("microsoft/phi-1_5")
  • Inference
  • Notebooks
  • Google Colab
  • Kaggle
  • Local Apps
  • vLLM

    How to use microsoft/phi-1_5 with vLLM:

    Install from pip and serve model
    # Install vLLM from pip:
    pip install vllm
    # Start the vLLM server:
    vllm serve "microsoft/phi-1_5"
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:8000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "microsoft/phi-1_5",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    Use Docker
    docker model run hf.co/microsoft/phi-1_5
  • SGLang

    How to use microsoft/phi-1_5 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-1_5" \
        --host 0.0.0.0 \
        --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "microsoft/phi-1_5",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
    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-1_5" \
            --host 0.0.0.0 \
            --port 30000
    # Call the server using curl (OpenAI-compatible API):
    curl -X POST "http://localhost:30000/v1/completions" \
    	-H "Content-Type: application/json" \
    	--data '{
    		"model": "microsoft/phi-1_5",
    		"prompt": "Once upon a time,",
    		"max_tokens": 512,
    		"temperature": 0.5
    	}'
  • Docker Model Runner

    How to use microsoft/phi-1_5 with Docker Model Runner:

    docker model run hf.co/microsoft/phi-1_5
New discussion
Resources
  • PR & discussions documentation
  • Code of Conduct
  • Hub documentation

Install & run microsoft/phi-1_5 easily using llmpm

#95 opened about 2 months ago by
sarthak-saxena

Prompt for GSM8K evaluations

#91 opened over 1 year ago by
dayvidwang

Phi 1.5 Instruct: an instruction following Phi 1.5 model that has undergone SFT and DPO

#89 opened almost 2 years ago by
rasyosef

Regarding the '/n' output

#87 opened almost 2 years ago by
DhruvSaraswat

[AUTOMATED] Model Memory Requirements

#86 opened about 2 years ago by
model-sizer-bot

The training time mentioned in the paper and the explanations in the Git repository have a significant gap.

1
#77 opened over 2 years ago by
wangzl

How to get model architecture/parameter names from the previous version

2
#76 opened over 2 years ago by
zekeZZ
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