Instructions to use internlm/CapRL-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use internlm/CapRL-3B with Transformers:

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

pipe = pipeline("image-text-to-text", model="internlm/CapRL-3B")
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, AutoModelForImageTextToText

processor = AutoProcessor.from_pretrained("internlm/CapRL-3B")
model = AutoModelForImageTextToText.from_pretrained("internlm/CapRL-3B")
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

vLLM

How to use internlm/CapRL-3B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "internlm/CapRL-3B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "internlm/CapRL-3B",
		"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/internlm/CapRL-3B

SGLang

How to use internlm/CapRL-3B 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 "internlm/CapRL-3B" \
    --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": "internlm/CapRL-3B",
		"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 "internlm/CapRL-3B" \
        --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": "internlm/CapRL-3B",
		"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 internlm/CapRL-3B with Docker Model Runner:
```
docker model run hf.co/internlm/CapRL-3B
```

nielsr HF Staff commited on Sep 30, 2025

Commit

5f835bb

verified ·

1 Parent(s): a38a4ba

Add link to GitHub code repository

Browse files

This PR adds an explicit link to the GitHub code repository for the CapRL project (`https://github.com/InternLM/CapRL`), making it easier for users to find and access the codebase.

No changes were made to the metadata or other existing content as they are already accurate and complete.

Files changed (1) hide show

README.md +4 -3

README.md CHANGED Viewed

@@ -1,18 +1,19 @@
 ---
-license: apache-2.0
 language:
 - en
 pipeline_tag: image-to-text
 tags:
 - multimodal
 - image caption
-library_name: transformers
 ---
 # CapRL-3B
 📖<a href="https://arxiv.org/abs/2509.22647">Paper</a> |🤗<a href="https://huggingface.co/internlm/CapRL-3B">CapRL-3B Model</a> |
   🤗<a href="https://huggingface.co/datasets/internlm/CapRL-2M">CapRL-2M Dataset</a> |🤗<a href="https://huggingface.co/collections/long-xing1/caprl-68d64ac32ded31596c36e189">CapRL Collection</a> | 🤗<a href="https://huggingface.co/papers/2509.22647">Daily Paper</a>
 ## Introduction
@@ -123,4 +124,4 @@ print("Chat response:", chat_response)
 </p>
 <p align="center">
   <img src="./assets/natural_caprl.png" alt="Main Results on GPT2" width="750"/>
-</p>

 ---
 language:
 - en
+library_name: transformers
+license: apache-2.0
 pipeline_tag: image-to-text
 tags:
 - multimodal
 - image caption
 ---
 # CapRL-3B
 📖<a href="https://arxiv.org/abs/2509.22647">Paper</a> |🤗<a href="https://huggingface.co/internlm/CapRL-3B">CapRL-3B Model</a> |
   🤗<a href="https://huggingface.co/datasets/internlm/CapRL-2M">CapRL-2M Dataset</a> |🤗<a href="https://huggingface.co/collections/long-xing1/caprl-68d64ac32ded31596c36e189">CapRL Collection</a> | 🤗<a href="https://huggingface.co/papers/2509.22647">Daily Paper</a>
+Code: https://github.com/InternLM/CapRL
 ## Introduction
 </p>
 <p align="center">
   <img src="./assets/natural_caprl.png" alt="Main Results on GPT2" width="750"/>
+</p>