Instructions to use kiel2/Kiel-2-OCR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use kiel2/Kiel-2-OCR with Transformers:

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

pipe = pipeline("image-text-to-text", model="kiel2/Kiel-2-OCR")
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)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("kiel2/Kiel-2-OCR", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use kiel2/Kiel-2-OCR with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf kiel2/Kiel-2-OCR:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf kiel2/Kiel-2-OCR:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf kiel2/Kiel-2-OCR:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf kiel2/Kiel-2-OCR:Q4_K_M

Build from source code

git clone https://github.com/ggml-org/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-app
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama serve -hf kiel2/Kiel-2-OCR:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama cli -hf kiel2/Kiel-2-OCR:Q4_K_M

Use Docker

docker model run hf.co/kiel2/Kiel-2-OCR:Q4_K_M

Llama new
LM Studio
Jan

vLLM

How to use kiel2/Kiel-2-OCR with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "kiel2/Kiel-2-OCR"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "kiel2/Kiel-2-OCR",
		"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/kiel2/Kiel-2-OCR:Q4_K_M

SGLang

How to use kiel2/Kiel-2-OCR 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 "kiel2/Kiel-2-OCR" \
    --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": "kiel2/Kiel-2-OCR",
		"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 "kiel2/Kiel-2-OCR" \
        --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": "kiel2/Kiel-2-OCR",
		"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"
						}
					}
				]
			}
		]
	}'

Ollama
How to use kiel2/Kiel-2-OCR with Ollama:
```
ollama run hf.co/kiel2/Kiel-2-OCR:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use kiel2/Kiel-2-OCR with Docker Model Runner:
```
docker model run hf.co/kiel2/Kiel-2-OCR:Q4_K_M
```

Lemonade

How to use kiel2/Kiel-2-OCR with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull kiel2/Kiel-2-OCR:Q4_K_M

Run and chat with the model

lemonade run user.Kiel-2-OCR-Q4_K_M

List all available models

lemonade list

Atomic Chat

Kiel-2-OCR

File size: 1,262 Bytes

32a8380

{
  "image_processor": {
    "do_convert_rgb": true,
    "do_normalize": true,
    "do_rescale": true,
    "do_resize": true,
    "image_mean": [
      0.48145466,
      0.4578275,
      0.40821073
    ],
    "image_processor_type": "Qwen2VLImageProcessor",
    "image_std": [
      0.26862954,
      0.26130258,
      0.27577711
    ],
    "merge_size": 2,
    "patch_size": 14,
    "resample": 3,
    "rescale_factor": 0.00392156862745098,
    "size": {
      "longest_edge": 401408,
      "shortest_edge": 200704
    },
    "temporal_patch_size": 2
  },
  "processor_class": "Qwen2_5_VLProcessor",
  "video_processor": {
    "do_convert_rgb": true,
    "do_normalize": true,
    "do_rescale": true,
    "do_resize": true,
    "do_sample_frames": false,
    "image_mean": [
      0.48145466,
      0.4578275,
      0.40821073
    ],
    "image_std": [
      0.26862954,
      0.26130258,
      0.27577711
    ],
    "max_frames": 768,
    "merge_size": 2,
    "min_frames": 4,
    "patch_size": 14,
    "resample": 3,
    "rescale_factor": 0.00392156862745098,
    "return_metadata": false,
    "size": {
      "longest_edge": 401408,
      "shortest_edge": 200704
    },
    "temporal_patch_size": 2,
    "video_processor_type": "Qwen2VLVideoProcessor"
  }
}