Instructions to use SkunkworksAI/phi-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SkunkworksAI/phi-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SkunkworksAI/phi-2", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("SkunkworksAI/phi-2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use SkunkworksAI/phi-2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SkunkworksAI/phi-2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SkunkworksAI/phi-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SkunkworksAI/phi-2
- SGLang
How to use SkunkworksAI/phi-2 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 "SkunkworksAI/phi-2" \ --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": "SkunkworksAI/phi-2", "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 "SkunkworksAI/phi-2" \ --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": "SkunkworksAI/phi-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SkunkworksAI/phi-2 with Docker Model Runner:
docker model run hf.co/SkunkworksAI/phi-2
| channels: | |
| - conda-forge | |
| dependencies: | |
| - python=3.10.11 | |
| - pip<=23.1.2 | |
| - pip: | |
| - mlflow==2.6.0 | |
| - cloudpickle==2.2.1 | |
| - jsonpickle==3.0.1 | |
| - mlflow-skinny==2.6.0 | |
| - azureml-core==1.51.0.post1 | |
| - azureml-mlflow==1.51.0 | |
| - azureml-metrics[all]==0.0.32 | |
| - scikit-learn==1.2.2 | |
| - cryptography==41.0.1 | |
| - python-dateutil==2.8.2 | |
| - datasets==2.14.6 | |
| - soundfile==0.12.1 | |
| - librosa==0.10.1 | |
| - diffusers==0.21.4 | |
| - sentencepiece==0.1.99 | |
| - transformers==4.34.0 | |
| - torch==2.1.0 | |
| - accelerate==0.23.0 | |
| - Pillow==9.4.0 | |
| - einops | |
| - azureml-evaluate-mlflow==0.0.32 | |
| name: mlflow-env | |