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
| flavors: | |
| hftransformersv2: | |
| code: null | |
| config_hf_load_kwargs: | |
| trust_remote_code: true | |
| hf_config_class: AutoConfig | |
| hf_pretrained_class: AutoModelForCausalLM | |
| hf_tokenizer_class: CodeGenTokenizerFast | |
| model_data: data | |
| model_hf_load_args: | |
| trust_remote_code: true | |
| pytorch_version: 2.1.0+cu118 | |
| task_type: text-generation | |
| tokenizer_hf_load_kwargs: | |
| trust_remote_code: true | |
| transformers_version: 4.34.0 | |
| python_function: | |
| data: data | |
| env: conda.yaml | |
| loader_module: azureml.evaluate.mlflow.hftransformers | |
| python_version: 3.10.11 | |
| mlflow_version: 2.6.0 | |
| model_uuid: 6068cffa9b034ea28c997f4538233299 | |
| utc_time_created: '2023-11-06 18:18:55.524636' | |