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
- 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
enable activation checkpointing
Browse files- modeling_phi.py +1 -2
modeling_phi.py
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@@ -525,7 +525,6 @@ class MHA(nn.Module):
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softmax_scale: Optional[float] = None,
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layer_idx: Optional[int] = None,
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return_residual: bool = False,
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checkpointing: bool = False,
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) -> None:
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super().__init__()
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@@ -585,7 +584,7 @@ class MHA(nn.Module):
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self.flash_attn = config.flash_attn and attn_cls is FlashSelfAttention
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self.layer_idx = layer_idx
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self.return_residual = return_residual
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self.checkpointing = checkpointing
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def _forward_self_attn(
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self, x: torch.FloatTensor, key_padding_mask: Optional[torch.BoolTensor]
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softmax_scale: Optional[float] = None,
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layer_idx: Optional[int] = None,
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return_residual: bool = False,
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) -> None:
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super().__init__()
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self.flash_attn = config.flash_attn and attn_cls is FlashSelfAttention
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self.layer_idx = layer_idx
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self.return_residual = return_residual
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+
self.checkpointing = getattr(config, "checkpointing", False)
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def _forward_self_attn(
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self, x: torch.FloatTensor, key_padding_mask: Optional[torch.BoolTensor]
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