Instructions to use HongxinLi/GoClick-Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use HongxinLi/GoClick-Large with Transformers:

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

pipe = pipeline("image-text-to-text", model="HongxinLi/GoClick-Large", trust_remote_code=True)

# Load model directly
from transformers import AutoProcessor, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("HongxinLi/GoClick-Large", trust_remote_code=True)
model = AutoModelForImageTextToText.from_pretrained("HongxinLi/GoClick-Large", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use HongxinLi/GoClick-Large with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/HongxinLi/GoClick-Large

SGLang

How to use HongxinLi/GoClick-Large 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 "HongxinLi/GoClick-Large" \
    --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": "HongxinLi/GoClick-Large",
		"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 "HongxinLi/GoClick-Large" \
        --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": "HongxinLi/GoClick-Large",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use HongxinLi/GoClick-Large with Docker Model Runner:
```
docker model run hf.co/HongxinLi/GoClick-Large
```

HongxinLi commited on 3 days ago

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Update README.md

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@@ -18,9 +18,10 @@ tags:
 [![GitHub](https://img.shields.io/badge/GitHub-Repo-black?logo=github)](https://github.com/ZJULiHongxin/GoClick)
 [![Paper](https://img.shields.io/badge/Paper-GoClick-blue?logo=adobeacrobatreader)](https://arxiv.org/abs/2604.23941)
-[![HuggingFace](https://img.shields.io/badge/🤗%20HuggingFace-Model-yellow)](https://huggingface.co/datasets/HongxinLi/GoClick-Large)
-[![HuggingFace](https://img.shields.io/badge/🤗%20HuggingFace-Dataset-yellow)](https://huggingface.co/datasets/HongxinLi/GoClick_Coreset_3814k)
-[![HuggingFace](https://img.shields.io/badge/🤗%20HuggingFace-SFTData-yellow)](https://huggingface.co/datasets/HongxinLi/GoClick_sft_data)
 </div>

 [![GitHub](https://img.shields.io/badge/GitHub-Repo-black?logo=github)](https://github.com/ZJULiHongxin/GoClick)
 [![Paper](https://img.shields.io/badge/Paper-GoClick-blue?logo=adobeacrobatreader)](https://arxiv.org/abs/2604.23941)
+[![GoClickLarge](https://img.shields.io/badge/🤗%20GoClickLarge-Model-yellow)](https://huggingface.co/HongxinLi/GoClick-Large)
+[![GoClickBase](https://img.shields.io/badge/🤗%20GoClickBase-Model-yellow)](https://huggingface.co/HongxinLi/GoClick-Base)
+[![SFTData](https://img.shields.io/badge/🤗%20SFT-Dataset-yellow)](https://huggingface.co/datasets/HongxinLi/GoClick_Coreset_3814k)
+[![SFTZipData](https://img.shields.io/badge/🤗%20SFTZip-SFTData-yellow)](https://huggingface.co/datasets/HongxinLi/GoClick_sft_data)
 </div>