Instructions to use WaltonFuture/Qwen2.5VL-3b-RLCS with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use WaltonFuture/Qwen2.5VL-3b-RLCS with Transformers:

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

pipe = pipeline("image-text-to-text", model="WaltonFuture/Qwen2.5VL-3b-RLCS")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
pipe(text=messages)

# Load model directly
from transformers import AutoProcessor, AutoModelForMultimodalLM

processor = AutoProcessor.from_pretrained("WaltonFuture/Qwen2.5VL-3b-RLCS")
model = AutoModelForMultimodalLM.from_pretrained("WaltonFuture/Qwen2.5VL-3b-RLCS")
messages = [
    {
        "role": "user",
        "content": [
            {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"},
            {"type": "text", "text": "What animal is on the candy?"}
        ]
    },
]
inputs = processor.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(processor.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use WaltonFuture/Qwen2.5VL-3b-RLCS with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "WaltonFuture/Qwen2.5VL-3b-RLCS"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "WaltonFuture/Qwen2.5VL-3b-RLCS",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Use Docker

docker model run hf.co/WaltonFuture/Qwen2.5VL-3b-RLCS

SGLang

How to use WaltonFuture/Qwen2.5VL-3b-RLCS 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 "WaltonFuture/Qwen2.5VL-3b-RLCS" \
    --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": "WaltonFuture/Qwen2.5VL-3b-RLCS",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

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 "WaltonFuture/Qwen2.5VL-3b-RLCS" \
        --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": "WaltonFuture/Qwen2.5VL-3b-RLCS",
		"messages": [
			{
				"role": "user",
				"content": [
					{
						"type": "text",
						"text": "Describe this image in one sentence."
					},
					{
						"type": "image_url",
						"image_url": {
							"url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg"
						}
					}
				]
			}
		]
	}'

Docker Model Runner
How to use WaltonFuture/Qwen2.5VL-3b-RLCS with Docker Model Runner:
```
docker model run hf.co/WaltonFuture/Qwen2.5VL-3b-RLCS
```

Improve model card with detailed description, usage, and additional info

by nielsr HF Staff - opened Jul 24, 2025

base: refs/heads/main

←

from: refs/pr/2

Discussion Files changed

+122

-3

Improve model card with detailed description, usage, and additional info3fd865d7

nielsr

Jul 24, 2025

This PR significantly enhances the model card by incorporating a detailed introduction, key highlights, and a practical Python code snippet for sample usage. It also includes comprehensive sections for data access, related model access, acknowledgments, and citation, all extracted from the original GitHub README. This update makes the model card more informative and user-friendly for researchers and developers on the Hugging Face Hub.

WaltonFuture changed pull request status to merged Jul 24, 2025

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