Instructions to use datalab-to/chandra-ocr-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use datalab-to/chandra-ocr-2 with Transformers:

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

pipe = pipeline("image-text-to-text", model="datalab-to/chandra-ocr-2")
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("datalab-to/chandra-ocr-2")
model = AutoModelForMultimodalLM.from_pretrained("datalab-to/chandra-ocr-2")
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 datalab-to/chandra-ocr-2 with vLLM:

Install from pip and serve model

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

SGLang

How to use datalab-to/chandra-ocr-2 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 "datalab-to/chandra-ocr-2" \
    --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": "datalab-to/chandra-ocr-2",
		"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 "datalab-to/chandra-ocr-2" \
        --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": "datalab-to/chandra-ocr-2",
		"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 datalab-to/chandra-ocr-2 with Docker Model Runner:
```
docker model run hf.co/datalab-to/chandra-ocr-2
```

Delores-Lin commited on 1 day ago

Commit

e51b498

verified ·

1 Parent(s): 808e461

Add MDPBench evaluation results

Browse files

Adds MDPBench benchmark results. Keeps source attribution on the overall leaderboard entry.

Files changed (1) hide show

.eval_results/mdpbench.yaml +135 -0

.eval_results/mdpbench.yaml ADDED Viewed

	@@ -0,0 +1,135 @@

+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: overall
+  value: 79.7
+  date: "2026-06-08"
+  source:
+    url: https://huggingface.co/datasets/Delores-Lin/MDPBench
+    name: MDPBench leaderboard
+    user: Delores-Lin
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: digital
+  value: 87.8
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: photographed
+  value: 77.1
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: latin
+  value: 82.7
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: de
+  value: 86.6
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: en
+  value: 86.5
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: es
+  value: 69.7
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: fr
+  value: 70.3
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: id
+  value: 84.6
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: it
+  value: 87.4
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: nl
+  value: 82.7
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: pt
+  value: 90.7
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: vi
+  value: 85.6
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: non_latin
+  value: 76.4
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: ar
+  value: 78.2
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: hi
+  value: 81.1
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: jp
+  value: 68.8
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: ko
+  value: 80.3
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: ru
+  value: 74.0
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: th
+  value: 78.5
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: zh
+  value: 73.8
+  date: "2026-06-08"
+- dataset:
+    id: Delores-Lin/MDPBench
+    task_id: zh_t
+  value: 76.3
+  date: "2026-06-08"