Instructions to use lightonai/LightOnOCR-2-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use lightonai/LightOnOCR-2-1B with Transformers:

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

pipe = pipeline("image-text-to-text", model="lightonai/LightOnOCR-2-1B")
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, AutoModelForSeq2SeqLM

processor = AutoProcessor.from_pretrained("lightonai/LightOnOCR-2-1B")
model = AutoModelForSeq2SeqLM.from_pretrained("lightonai/LightOnOCR-2-1B")
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 lightonai/LightOnOCR-2-1B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "lightonai/LightOnOCR-2-1B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "lightonai/LightOnOCR-2-1B",
		"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/lightonai/LightOnOCR-2-1B

SGLang

How to use lightonai/LightOnOCR-2-1B 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 "lightonai/LightOnOCR-2-1B" \
    --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": "lightonai/LightOnOCR-2-1B",
		"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 "lightonai/LightOnOCR-2-1B" \
        --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": "lightonai/LightOnOCR-2-1B",
		"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 lightonai/LightOnOCR-2-1B with Docker Model Runner:
```
docker model run hf.co/lightonai/LightOnOCR-2-1B
```

nielsr HF Staff commited on Feb 19

Commit

aaebe21

verified ·

1 Parent(s): e6039be

Add overall OlmOCRBench results

Browse files

OlmOCRBench was recently updated to display "Overall" results by default, this PR ensures your model shows its score on the leaderboard.

It will show up here: https://huggingface.co/datasets/allenai/olmOCR-bench.

Files changed (1) hide show

.eval_results/olmocrbench.yaml +8 -6

.eval_results/olmocrbench.yaml CHANGED Viewed

@@ -1,8 +1,15 @@
 - dataset:
     id: allenai/olmOCR-bench
     task_id: arxiv_math
   value: 89.6
-  date: '2025-10-22'
   source:
     url: https://huggingface.co/papers/2601.14251
     name: LightOnOCR technical report
@@ -11,7 +18,6 @@
     id: allenai/olmOCR-bench
     task_id: old_scans_math
   value: 85.6
-  date: '2025-10-22'
   source:
     url: https://huggingface.co/papers/2601.14251
     name: LightOnOCR technical report
@@ -20,7 +26,6 @@
     id: allenai/olmOCR-bench
     task_id: table_tests
   value: 89.0
-  date: '2025-10-22'
   source:
     url: https://huggingface.co/papers/2601.14251
     name: LightOnOCR technical report
@@ -29,7 +34,6 @@
     id: allenai/olmOCR-bench
     task_id: old_scans
   value: 42.2
-  date: '2025-10-22'
   source:
     url: https://huggingface.co/papers/2601.14251
     name: LightOnOCR technical report
@@ -38,7 +42,6 @@
     id: allenai/olmOCR-bench
     task_id: multi_column
   value: 84.8
-  date: '2025-10-22'
   source:
     url: https://huggingface.co/papers/2601.14251
     name: LightOnOCR technical report
@@ -47,7 +50,6 @@
     id: allenai/olmOCR-bench
     task_id: long_tiny_text
   value: 91.4
-  date: '2025-10-22'
   source:
     url: https://huggingface.co/papers/2601.14251
     name: LightOnOCR technical report

+- dataset:
+    id: allenai/olmOCR-bench
+    task_id: overall
+  value: 83.2
+  source:
+    url: https://huggingface.co/papers/2601.14251
+    name: LightOnOCR technical report
+    user: nielsr
 - dataset:
     id: allenai/olmOCR-bench
     task_id: arxiv_math
   value: 89.6
   source:
     url: https://huggingface.co/papers/2601.14251
     name: LightOnOCR technical report
     id: allenai/olmOCR-bench
     task_id: old_scans_math
   value: 85.6
   source:
     url: https://huggingface.co/papers/2601.14251
     name: LightOnOCR technical report
     id: allenai/olmOCR-bench
     task_id: table_tests
   value: 89.0
   source:
     url: https://huggingface.co/papers/2601.14251
     name: LightOnOCR technical report
     id: allenai/olmOCR-bench
     task_id: old_scans
   value: 42.2
   source:
     url: https://huggingface.co/papers/2601.14251
     name: LightOnOCR technical report
     id: allenai/olmOCR-bench
     task_id: multi_column
   value: 84.8
   source:
     url: https://huggingface.co/papers/2601.14251
     name: LightOnOCR technical report
     id: allenai/olmOCR-bench
     task_id: long_tiny_text
   value: 91.4
   source:
     url: https://huggingface.co/papers/2601.14251
     name: LightOnOCR technical report