Instructions to use microsoft/phi-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/phi-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="microsoft/phi-2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-2") model = AutoModelForCausalLM.from_pretrained("microsoft/phi-2") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use microsoft/phi-2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "microsoft/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": "microsoft/phi-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/microsoft/phi-2
- SGLang
How to use microsoft/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 "microsoft/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": "microsoft/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 "microsoft/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": "microsoft/phi-2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use microsoft/phi-2 with Docker Model Runner:
docker model run hf.co/microsoft/phi-2
Query!! Kindly let me know the alternative.
For Fine-Tuning (Using PEFT) code :
from peft import prepare_model_for_kbit_training
model.gradient_checkpointing_enable()
model = prepare_model_for_kbit_training(model)
Error :
ValueError Traceback (most recent call last)
in <cell line: 3>()
1 from peft import prepare_model_for_kbit_training
2
----> 3 model.gradient_checkpointing_enable()
4 model = prepare_model_for_kbit_training(model)
/usr/local/lib/python3.10/dist-packages/transformers/modeling_utils.py in gradient_checkpointing_enable(self)
1629 """
1630 if not self.supports_gradient_checkpointing:
-> 1631 raise ValueError(f"{self.class.name} does not support gradient checkpointing.")
1632 self.apply(partial(self._set_gradient_checkpointing, value=True))
1633
ValueError: PhiForCausalLM does not support gradient checkpointing.
Kindly let me know how to solve this issue.
Thank You
Email ID - tushar.paul@kusho.co
I also meet this issue. And i do not know how to solve it.
Hello @ilovestudy and @tusharpaul .
We will proceed with the integration of Phi directly in transformers and it will fix the gradient checkpointing issue.