Text Generation
Transformers
Safetensors
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phi3
nlp
code
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text-generation-inference
Instructions to use microsoft/Phi-3-mini-128k-instruct with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/Phi-3-mini-128k-instruct with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="microsoft/Phi-3-mini-128k-instruct", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-128k-instruct", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-128k-instruct", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use microsoft/Phi-3-mini-128k-instruct with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "microsoft/Phi-3-mini-128k-instruct" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "microsoft/Phi-3-mini-128k-instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/microsoft/Phi-3-mini-128k-instruct
- SGLang
How to use microsoft/Phi-3-mini-128k-instruct 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-3-mini-128k-instruct" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "microsoft/Phi-3-mini-128k-instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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-3-mini-128k-instruct" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "microsoft/Phi-3-mini-128k-instruct", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use microsoft/Phi-3-mini-128k-instruct with Docker Model Runner:
docker model run hf.co/microsoft/Phi-3-mini-128k-instruct
Pipeline tokenizer does not get initialized when loading from string
#50
by connorboyle - opened
If I try loading a pipeline for this model:
>>> pipe = pipeline(model="microsoft/Phi-3-mini-128k-instruct", trust_remote_code=True)
the tokenizer is initialized to None and the pipeline cannot be called without crashing.
>>> type(pipe.tokenizer)
NoneType
>>> pipe("Hello, world")
...
TypeError: 'NoneType' object is not callable
however, if the tokenizer is manually initialized, the pipeline can be called as normal:
>>> pipe = pipeline(model="microsoft/Phi-3-mini-128k-instruct", tokenizer=AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-128k-instruct"), trust_remote_code=True)
>>> pipe("Hello, world")
[{'generated_text': 'Hello, world!\n\n### Exercises\n\n1. Write a Python program'}]
connorboyle changed discussion title from Pipeline does not work when loading from string to Pipeline tokenizer does not initialized when loading from string
It's possibly due to trust_remote_code=True. Should work as soon as HF releases their 4.41.0 version.
connorboyle changed discussion title from Pipeline tokenizer does not initialized when loading from string to Pipeline tokenizer does not get initialized when loading from string
nguyenbh changed discussion status to closed