Instructions to use leliuga/phi-2-bnb-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use leliuga/phi-2-bnb-4bit with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="leliuga/phi-2-bnb-4bit", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("leliuga/phi-2-bnb-4bit", trust_remote_code=True)
model = AutoModelForMultimodalLM.from_pretrained("leliuga/phi-2-bnb-4bit", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use leliuga/phi-2-bnb-4bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "leliuga/phi-2-bnb-4bit"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "leliuga/phi-2-bnb-4bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/leliuga/phi-2-bnb-4bit

SGLang

How to use leliuga/phi-2-bnb-4bit 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 "leliuga/phi-2-bnb-4bit" \
    --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": "leliuga/phi-2-bnb-4bit",
		"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 "leliuga/phi-2-bnb-4bit" \
        --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": "leliuga/phi-2-bnb-4bit",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use leliuga/phi-2-bnb-4bit with Docker Model Runner:
```
docker model run hf.co/leliuga/phi-2-bnb-4bit
```

phi-2 - bnb 4bit

Model creator: Microsoft
Original model: phi-2

Description

This model is 4bit quantized version of phi-2 using bitsandbytes. It's designed for fine-tuning! The PAD token is set as "<|endoftext|>".

Downloads last month: 3

Safetensors

Model size

3B params

Tensor type

F32

F16

Model tree for leliuga/phi-2-bnb-4bit

Base model

microsoft/phi-2

Quantized

(59)

this model

Collection including leliuga/phi-2-bnb-4bit

bnb-4 bit

Collection

A 4-bit quantized version models designed for fine-tuning. Demo: https://colab.research.google.com/drive/19UpFUjtbJoLua-4DMb1JKKwJAcvMyMHb • 20 items • Updated Mar 2