Instructions to use BoyaWu10/bunny-pretrain-phi-3-siglip with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use BoyaWu10/bunny-pretrain-phi-3-siglip with Transformers:

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

pipe = pipeline("text-generation", model="BoyaWu10/bunny-pretrain-phi-3-siglip", trust_remote_code=True)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("BoyaWu10/bunny-pretrain-phi-3-siglip", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use BoyaWu10/bunny-pretrain-phi-3-siglip with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "BoyaWu10/bunny-pretrain-phi-3-siglip"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "BoyaWu10/bunny-pretrain-phi-3-siglip",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/BoyaWu10/bunny-pretrain-phi-3-siglip

SGLang

How to use BoyaWu10/bunny-pretrain-phi-3-siglip 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 "BoyaWu10/bunny-pretrain-phi-3-siglip" \
    --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": "BoyaWu10/bunny-pretrain-phi-3-siglip",
		"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 "BoyaWu10/bunny-pretrain-phi-3-siglip" \
        --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": "BoyaWu10/bunny-pretrain-phi-3-siglip",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use BoyaWu10/bunny-pretrain-phi-3-siglip with Docker Model Runner:
```
docker model run hf.co/BoyaWu10/bunny-pretrain-phi-3-siglip
```

bunny-pretrain-phi-3-siglip / README.md

Isaachhe

init

7adf7c2 over 2 years ago

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	---
	inference: false
	license: apache-2.0
	---

	# Model Card

	Bunny is a family of lightweight multimodal models.

	Bunny-pretrain-phi-3-siglip is the pretrained weights for [Bunny-v1.0-4B](https://huggingface.co/BAAI/Bunny-v1_0-4B), which leverages Phi-3-Mini-4K-Instruct as the language model backbone and SigLIP as the vision encoder.
	It is pretrained on LAION-2M.

	More details about this model can be found in [GitHub](https://github.com/BAAI-DCAI/Bunny).

	# License
	This project utilizes certain datasets and checkpoints that are subject to their respective original licenses. Users must comply with all terms and conditions of these original licenses.
	The content of this project itself is licensed under the Apache license 2.0.