Image-Text-to-Text
GGUF
German
English
ocr
vision
german
invoice-extraction
llama-cpp
ollama
conversational
Instructions to use Keyven/german-ocr-3.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Keyven/german-ocr-3.1 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Keyven/german-ocr-3.1", filename="german-ocr-3.1-F16.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
- llama.cpp
How to use Keyven/german-ocr-3.1 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-3.1:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Keyven/german-ocr-3.1:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Keyven/german-ocr-3.1:Q4_K_M # Run inference directly in the terminal: llama-cli -hf Keyven/german-ocr-3.1:Q4_K_M
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-3.1:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Keyven/german-ocr-3.1:Q4_K_M
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-3.1:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Keyven/german-ocr-3.1:Q4_K_M
Use Docker
docker model run hf.co/Keyven/german-ocr-3.1:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use Keyven/german-ocr-3.1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Keyven/german-ocr-3.1" # 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-3.1", "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-3.1:Q4_K_M
- Ollama
How to use Keyven/german-ocr-3.1 with Ollama:
ollama run hf.co/Keyven/german-ocr-3.1:Q4_K_M
- Unsloth Studio new
How to use Keyven/german-ocr-3.1 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-3.1 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-3.1 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-3.1 to start chatting
- Docker Model Runner
How to use Keyven/german-ocr-3.1 with Docker Model Runner:
docker model run hf.co/Keyven/german-ocr-3.1:Q4_K_M
- Lemonade
How to use Keyven/german-ocr-3.1 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Keyven/german-ocr-3.1:Q4_K_M
Run and chat with the model
lemonade run user.german-ocr-3.1-Q4_K_M
List all available models
lemonade list
| {%- set DEFAULT_SYSTEM = "Du bist German-OCR-3.1, das deutsche Vision- und OCR-Modell von Keyvan.ai. Aufgabe: Lies das uebergebene Bild eines deutschen Geschaeftsdokuments (Rechnung, Brief, Formular, Quittung, Bescheid) und extrahiere strukturierte Daten als sauberes JSON. Keine Erklaerung, kein Markdown, keine Codefence — NUR ein einziges JSON-Objekt. WENN ein Wert nicht im Bild steht, gib null. Bevorzuge null vor halluzinierten Werten. Originalschreibweise und Umlaute beibehalten. Datumsangaben YYYY-MM-DD wenn eindeutig. Geldbetraege als Dezimal mit Punkt. Waehrung als ISO-Code (EUR). Bei freien Text-Anweisungen ohne Bild: antworte praezise und knapp auf Deutsch." -%} | |
| {%- if messages and messages[0]['role'] == 'system' -%} | |
| <|im_start|>system | |
| {% if messages[0]['content'] is string %}{{ messages[0]['content'] }}{% else %}{% for c in messages[0]['content'] %}{% if c.type == 'text' %}{{ c.text }}{% endif %}{% endfor %}{% endif %}<|im_end|> | |
| {% set messages = messages[1:] %} | |
| {%- else -%} | |
| <|im_start|>system | |
| {{ DEFAULT_SYSTEM }}<|im_end|> | |
| {%- endif -%} | |
| {%- for message in messages -%} | |
| <|im_start|>{{ message['role'] }} | |
| {% if message['content'] is string %}{{ message['content'] }}{% else %}{% for c in message['content'] %}{% if c.type == 'text' %}{{ c.text }}{% elif c.type == 'image' %}<|vision_start|><|image_pad|><|vision_end|>{% endif %}{% endfor %}{% endif %}<|im_end|> | |
| {% endfor -%} | |
| {%- if add_generation_prompt -%} | |
| <|im_start|>assistant | |
| {% endif -%} | |