Instructions to use microsoft/phi-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/phi-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="microsoft/phi-1")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("microsoft/phi-1") model = AutoModelForCausalLM.from_pretrained("microsoft/phi-1", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use microsoft/phi-1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "microsoft/phi-1" # 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", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/microsoft/phi-1
- SGLang
How to use microsoft/phi-1 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" \ --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", "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" \ --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", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use microsoft/phi-1 with Docker Model Runner:
docker model run hf.co/microsoft/phi-1
fix(phi-1): Checks length of `attention_mask`if it is passed as direct tensor.
Browse files
modeling_mixformer_sequential.py
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import math
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import copy
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from typing import Any, Dict, Optional, Tuple
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from dataclasses import dataclass, field
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import torch
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kv = update_kv_cache(qkv[:, :, 1:], past_key_values, self.layer_idx)
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if attention_mask is not None:
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attention_mask
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attention_mask = attention_mask.to(qkv.device)
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attention_kwargs = {"attention_mask": attention_mask}
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import math
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import copy
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from typing import Any, Dict, Optional, Tuple, Union
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from dataclasses import dataclass, field
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import torch
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kv = update_kv_cache(qkv[:, :, 1:], past_key_values, self.layer_idx)
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if attention_mask is not None:
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attention_mask = attention_mask[0] if isinstance(attention_mask, tuple) else attention_mask
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attention_mask = attention_mask.bool().to(qkv.device)
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attention_kwargs = {"attention_mask": attention_mask}
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