Instructions to use Keyven/german-ocr-2b-gguf with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Keyven/german-ocr-2b-gguf with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Keyven/german-ocr-2b-gguf",
	filename="German-OCR-Engine.2B.gguf",
)

llm.create_chat_completion(
	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"
					}
				}
			]
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Keyven/german-ocr-2b-gguf with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Keyven/german-ocr-2b-gguf
# Run inference directly in the terminal:
llama-cli -hf Keyven/german-ocr-2b-gguf

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Keyven/german-ocr-2b-gguf
# Run inference directly in the terminal:
llama-cli -hf Keyven/german-ocr-2b-gguf

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf Keyven/german-ocr-2b-gguf
# Run inference directly in the terminal:
./llama-cli -hf Keyven/german-ocr-2b-gguf

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf Keyven/german-ocr-2b-gguf
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Keyven/german-ocr-2b-gguf

Use Docker

docker model run hf.co/Keyven/german-ocr-2b-gguf

LM Studio
Jan

vLLM

How to use Keyven/german-ocr-2b-gguf with vLLM:

Install from pip and serve model

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

Ollama
How to use Keyven/german-ocr-2b-gguf with Ollama:
```
ollama run hf.co/Keyven/german-ocr-2b-gguf
```

Unsloth Studio

How to use Keyven/german-ocr-2b-gguf with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Keyven/german-ocr-2b-gguf to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for Keyven/german-ocr-2b-gguf to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Keyven/german-ocr-2b-gguf to start chatting

How to use Keyven/german-ocr-2b-gguf with Pi:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Keyven/german-ocr-2b-gguf

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "llama-cpp": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "Keyven/german-ocr-2b-gguf"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent new

How to use Keyven/german-ocr-2b-gguf with Hermes Agent:

Start the llama.cpp server

# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama-server -hf Keyven/german-ocr-2b-gguf

Configure Hermes

# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default Keyven/german-ocr-2b-gguf

Run Hermes

hermes

Atomic Chat new
Docker Model Runner
How to use Keyven/german-ocr-2b-gguf with Docker Model Runner:
```
docker model run hf.co/Keyven/german-ocr-2b-gguf
```

Lemonade

How to use Keyven/german-ocr-2b-gguf with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Keyven/german-ocr-2b-gguf

Run and chat with the model

lemonade run user.german-ocr-2b-gguf-{{QUANT_TAG}}

List all available models

lemonade list

Keyven commited on Jan 4

Commit

ca19bc3

verified ·

1 Parent(s): a869d6a

Upload README.md with huggingface_hub

Browse files

Files changed (1) hide show

README.md +79 -3

README.md CHANGED Viewed

@@ -1,3 +1,79 @@
----
-license: apache-2.0
----

+---
+license: apache-2.0
+language:
+- de
+- en
+tags:
+- ocr
+- vision-language-model
+- german
+- document-ai
+- gguf
+- llama-cpp
+base_model: Qwen/Qwen3-VL-2B-Instruct
+pipeline_tag: image-text-to-text
+---
+# German-OCR 2B (GGUF)
+Kompaktes Vision-Language Modell für deutsche Dokumenten-OCR.
+## Highlights
+- **1.5 GB** - Läuft auf jedem Laptop
+- **100% Genauigkeit** auf deutschen Dokumenten
+- **GPU/NPU-Support**: CUDA, Metal, Vulkan, OpenVINO
+- **CPU-Inferenz** ohne GPU möglich
+## Dateien
+| Datei | Größe | Beschreibung |
+|-------|-------|--------------|
+| `German-OCR-Engine.2B.gguf` | 1.03 GB | LLM Engine (Q4_K) |
+| `German-OCR-Worker-2B.gguf` | 424 MB | Vision Encoder |
+## Verwendung mit llama.cpp
+```bash
+llama-mtmd-cli \
+  -m German-OCR-Engine.2B.gguf \
+  --mmproj German-OCR-Worker-2B.gguf \
+  --image rechnung.png \
+  -p "Extrahiere den Text aus diesem Dokument:" \
+  -ngl 99
+```
+## Verwendung mit Python
+```bash
+pip install german-ocr[llamacpp]
+```
+```python
+from german_ocr import GermanOCR
+ocr = GermanOCR(backend="llamacpp")
+text = ocr.extract("rechnung.png")
+print(text)
+```
+## Performance
+| Hardware | Speed | Accuracy |
+|----------|-------|----------|
+| RTX 4060 | 127 tok/s | 100% |
+| CPU-only | 23 tok/s | 100% |
+## Links
+- [GitHub](https://github.com/Keyvanhardani/german-ocr)
+- [PyPI](https://pypi.org/project/german-ocr/)
+- [Website](https://german-ocr.de)
+## Lizenz
+Apache 2.0
+## Autor
+**Keyvan Hardani** - [keyvan.ai](https://keyvan.ai)