Instructions to use TomasFAV/DonutInvoiceCzechV03 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TomasFAV/DonutInvoiceCzechV03 with Transformers:

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

pipe = pipeline("image-text-to-text", model="TomasFAV/DonutInvoiceCzechV03")

# Load model directly
from transformers import AutoTokenizer, AutoModelForImageTextToText

tokenizer = AutoTokenizer.from_pretrained("TomasFAV/DonutInvoiceCzechV03")
model = AutoModelForImageTextToText.from_pretrained("TomasFAV/DonutInvoiceCzechV03")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use TomasFAV/DonutInvoiceCzechV03 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TomasFAV/DonutInvoiceCzechV03"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TomasFAV/DonutInvoiceCzechV03",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/TomasFAV/DonutInvoiceCzechV03

SGLang

How to use TomasFAV/DonutInvoiceCzechV03 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 "TomasFAV/DonutInvoiceCzechV03" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TomasFAV/DonutInvoiceCzechV03",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "TomasFAV/DonutInvoiceCzechV03" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TomasFAV/DonutInvoiceCzechV03",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use TomasFAV/DonutInvoiceCzechV03 with Docker Model Runner:
```
docker model run hf.co/TomasFAV/DonutInvoiceCzechV03
```

DonutInvoiceCzechV03

File size: 555 Bytes

00586f7

{
  "image_processor": {
    "data_format": "channels_first",
    "do_align_long_axis": false,
    "do_normalize": true,
    "do_pad": true,
    "do_rescale": true,
    "do_resize": true,
    "do_thumbnail": true,
    "image_mean": [
      0.5,
      0.5,
      0.5
    ],
    "image_processor_type": "DonutImageProcessorFast",
    "image_std": [
      0.5,
      0.5,
      0.5
    ],
    "resample": 2,
    "rescale_factor": 0.00392156862745098,
    "size": {
      "height": 2338,
      "width": 1654
    }
  },
  "processor_class": "DonutProcessor"
}