Instructions to use radames/phi-2-quantized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use radames/phi-2-quantized with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="radames/phi-2-quantized", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("radames/phi-2-quantized", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use radames/phi-2-quantized with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "radames/phi-2-quantized" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "radames/phi-2-quantized", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/radames/phi-2-quantized
- SGLang
How to use radames/phi-2-quantized 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 "radames/phi-2-quantized" \ --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": "radames/phi-2-quantized", "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 "radames/phi-2-quantized" \ --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": "radames/phi-2-quantized", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use radames/phi-2-quantized with Docker Model Runner:
docker model run hf.co/radames/phi-2-quantized
Need help with quantizing the original model
Can someone provide instructions on how the original model can be quantized?
I downloaded the model from microsoft/phi-2 and tried to quantize it using the scripts in llama.cpp but got an error only to realize the model is not yet supported on llama.cpp.
Any insights or suggestions would be greatly appreciated.
I think python code is used maybe python transformers library or the one used in example code
Robin Kroonem in TheBloke/phi-2-GPTQ release discussion mentioned a change to fix it https://github.com/mrgraycode/llama.cpp/commit/12cc80cb8975aea3bc9f39d3c9b84f7001ab94c5#diff-150dc86746a90bad4fc2c3334aeb9b5887b3adad3cc1459446717638605348efR6239