Image-Text-to-Text
GGUF
German
English
ocr
vision
german
invoice-extraction
llama-cpp
ollama
conversational
Instructions to use keyvan-ai/german-ocr-3.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use keyvan-ai/german-ocr-3.1 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 keyvan-ai/german-ocr-3.1:Q4_K_M # Run inference directly in the terminal: llama cli -hf keyvan-ai/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 serve -hf keyvan-ai/german-ocr-3.1:Q4_K_M # Run inference directly in the terminal: llama cli -hf keyvan-ai/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 keyvan-ai/german-ocr-3.1:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf keyvan-ai/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 keyvan-ai/german-ocr-3.1:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf keyvan-ai/german-ocr-3.1:Q4_K_M
Use Docker
docker model run hf.co/keyvan-ai/german-ocr-3.1:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use keyvan-ai/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 "keyvan-ai/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": "keyvan-ai/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/keyvan-ai/german-ocr-3.1:Q4_K_M
- Ollama
How to use keyvan-ai/german-ocr-3.1 with Ollama:
ollama run hf.co/keyvan-ai/german-ocr-3.1:Q4_K_M
- Unsloth Studio
How to use keyvan-ai/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 keyvan-ai/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 keyvan-ai/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 keyvan-ai/german-ocr-3.1 to start chatting
- Docker Model Runner
How to use keyvan-ai/german-ocr-3.1 with Docker Model Runner:
docker model run hf.co/keyvan-ai/german-ocr-3.1:Q4_K_M
- Lemonade
How to use keyvan-ai/german-ocr-3.1 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull keyvan-ai/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
- Atomic Chat
| license: apache-2.0 | |
| language: | |
| - de | |
| - en | |
| tags: | |
| - ocr | |
| - vision | |
| - german | |
| - invoice-extraction | |
| - gguf | |
| - llama-cpp | |
| - ollama | |
| pipeline_tag: image-text-to-text | |
| # 👁 German-OCR-3.1 | |
| > **Das deutsche Vision-OCR-Modell von [Keyvan.ai](https://german-ocr.de) — Teil der German-OCR-3 Kollektion.** | |
| ```bash | |
| ollama run Keyvan/german-ocr-3.1 | |
| ``` | |
| --- | |
| ## Die Geschichte | |
| German-OCR-3 begann als kleine Idee: ein Modell, das **deutsche Geschäftsdokumente** | |
| wirklich versteht — Rechnungen, Briefe, Bescheide, Quittungen, Verträge. | |
| Nicht „auch deutsch", sondern auf deutsche Bürokratie und deutsches Layout spezialisiert. | |
| Die **3.1-Generation** ist die feinabgestimmte, engineered + optimierte Version dieser | |
| Kollektion. Zwei spezialisierte Modelle: | |
| | Modell | Rolle | | |
| |---|---| | |
| | **👁 German-OCR-3.1** *(du bist hier)* | Vision-OCR — Bild rein, sauberes JSON raus | | |
| | 🇩🇪 [**German-Text-3.1**](https://ollama.com/Keyvan/german-text-3.1) | Text-Assistent für Übersetzung, Zusammenfassung, Analyse, Chat | | |
| OCR-3.1 wurde mit harten Regeln für **Halluzinations-Vermeidung** konfiguriert: | |
| lieber `null` als geraten, Originalschreibweise behalten, sender vs. recipient | |
| sauber trennen — das alles ist Pflicht in der Engineering-Konfiguration. | |
| --- | |
| ## ✨ Was kann das Modell? | |
| **Bild rein → Strukturiertes JSON raus.** | |
| | Doc-Typ | Erkennt | | |
| |---|---| | |
| | 🧾 **Rechnung** | sender, recipient, IBAN, USt-ID, line_items, amount_net/vat/total, due_date, payment_terms | | |
| | 📬 **Brief** | sender, recipient, Betreff, Datum, Aktenzeichen | | |
| | 📋 **Formular** | Felder, Werte, Unterschriften-Felder | | |
| | 🧾 **Quittung** | Händler, Datum, Positionen, Summe, Steuersatz | | |
| | ⚖️ **Bescheid** | Behörde, Aktenzeichen, Empfänger, Betrag, Frist | | |
| | 📄 **Vertrag** | Parteien, Datum, Schlüsselklauseln | | |
| ### JSON Output Schema | |
| ```json | |
| { | |
| "document_type": "invoice", | |
| "language": "de", | |
| "invoice_number": "...", | |
| "invoice_date": "YYYY-MM-DD", | |
| "due_date": "YYYY-MM-DD", | |
| "sender": {"name": "...", "address": "...", "vat_id": "...", "iban": "..."}, | |
| "recipient": {"name": "...", "address": "...", "customer_id": "..."}, | |
| "line_items": [ | |
| {"position": 1, "description": "...", "quantity": 1, "unit": "Stueck", | |
| "unit_price_net": 0.00, "amount_net": 0.00, "vat_rate": 19} | |
| ], | |
| "amount_net": 0.00, "amount_vat": 0.00, "amount_total": 0.00, | |
| "currency": "EUR", | |
| "notes": [] | |
| } | |
| ``` | |
| **Garantien:** | |
| - ✅ JSON-Validität | |
| - ✅ `null` statt erfundener Werte (Halluzinations-Stop-Regel) | |
| - ✅ Originalschreibweise + Umlaute | |
| - ✅ ISO-Datum, Punkt-Dezimal, EUR-Code | |
| - ✅ sender ≠ recipient klar getrennt | |
| --- | |
| ## 🚀 Quick Start | |
| ### Ollama (1 Zeile) | |
| ```bash | |
| ollama run Keyvan/german-ocr-3.1 | |
| ``` | |
| API mit Bild: | |
| ```bash | |
| curl http://localhost:11434/api/chat -d '{ | |
| "model": "Keyvan/german-ocr-3.1", | |
| "messages": [{ | |
| "role": "user", | |
| "content": "Extrahiere als JSON.", | |
| "images": ["BASE64_IMAGE_HERE"] | |
| }], | |
| "think": false | |
| }' | |
| ``` | |
| ### llama-server (HF GGUF, Two-File-Pattern) | |
| ```bash | |
| hf download Keyven/german-ocr-3.1 \ | |
| german-ocr-3.1-Q8_0.gguf \ | |
| mmproj-german-ocr-3.1-F16.gguf | |
| llama-server \ | |
| -m german-ocr-3.1-Q8_0.gguf \ | |
| --mmproj mmproj-german-ocr-3.1-F16.gguf \ | |
| --port 8080 -ngl 99 | |
| ``` | |
| --- | |
| ## 📦 Files (auf [HuggingFace](https://huggingface.co/Keyven/german-ocr-3.1)) | |
| | File | Größe | Use case | | |
| |---|---|---| | |
| | `german-ocr-3.1-Q4_K_M.gguf` | 941 MB | Compact / Edge | | |
| | `german-ocr-3.1-Q8_0.gguf` | 1.6 GB | ⭐ **Recommended** | | |
| | `german-ocr-3.1-F16.gguf` | 2.9 GB | Full precision | | |
| | `mmproj-german-ocr-3.1-F16.gguf` | 1.3 GB | **Required** für Vision (llama-server) | | |
| > **Hinweis**: Über Ollama Hub bekommst du das Modell als single-package mit Vision — | |
| > der mmproj-Sidecar wird nur für die manuelle llama-server-Route benötigt. | |
| --- | |
| ## 🛠 Hardware | |
| | Variant | RAM (CPU) | VRAM (GPU) | | |
| |---|---|---| | |
| | Q4 + Vision | 4 GB | 4 GB | | |
| | Q8 + Vision | 6 GB | 6 GB | | |
| | F16 + Vision | 10 GB | 10 GB | | |
| GPU empfohlen für Echtzeit-OCR. Context: **32 768 Tokens**. | |
| --- | |
| ## 🤝 German-OCR Familie | |
| | | Was | Wo | | |
| |---|---|---| | |
| | 👁 **German-OCR-3.1** | Vision-OCR (du bist hier) | [ollama.com](https://ollama.com/Keyvan/german-ocr-3.1) · [HF](https://huggingface.co/Keyven/german-ocr-3.1) | | |
| | 🇩🇪 **German-Text-3.1** | Text-Assistent | [ollama.com](https://ollama.com/Keyvan/german-text-3.1) · [HF](https://huggingface.co/Keyven/german-text-3.1) | | |
| | ☁️ **German-OCR Cloud API** | Managed Service mit höherer Genauigkeit | [german-ocr.de](https://german-ocr.de) | | |
| | 📝 **German-OCR for Word** | Office Add-in | [office.german-ocr.de](https://office.german-ocr.de) | | |
| --- | |
| ## 📜 License & Credits | |
| **Apache License 2.0** — kommerzielle Nutzung mit Attribution erlaubt. | |
| **NOTICE**: Aufgebaut auf [Qwen3.5](https://qwenlm.github.io/) von Alibaba Cloud. | |
| Die German-OCR-3.1-Kollektion ist eine in Deutschland engineered + optimierte | |
| Distribution für deutsche Geschäftsdokumente. Architecture credit: Qwen Team. | |
| Build mit ❤️ in 🇩🇪 von **[Keyvan Hardani](https://german-ocr.de)**. | |