Instructions to use fangrayson/donut-base-funsd with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use fangrayson/donut-base-funsd with Transformers:

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

pipe = pipeline("image-text-to-text", model="fangrayson/donut-base-funsd")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("fangrayson/donut-base-funsd")
model = AutoModelForMultimodalLM.from_pretrained("fangrayson/donut-base-funsd", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use fangrayson/donut-base-funsd with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/fangrayson/donut-base-funsd

SGLang

How to use fangrayson/donut-base-funsd 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 "fangrayson/donut-base-funsd" \
    --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": "fangrayson/donut-base-funsd",
		"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 "fangrayson/donut-base-funsd" \
        --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": "fangrayson/donut-base-funsd",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use fangrayson/donut-base-funsd with Docker Model Runner:
```
docker model run hf.co/fangrayson/donut-base-funsd
```

donut-base-funsd

Commit History

Feb 20, 2025

00:55
Adding `safetensors` variant of this model⁠

SFconvertbot

Verified signature
908286b

Apr 5, 2023

07:59
Training done (#3)⁠

fangrayson

1a9d94a
07:59
Training done (#2)⁠

fangrayson

2b9e5d4
07:59
Training in progress, epoch 0 (#1)⁠

fangrayson

4a7a1b8
07:48
initial commit

fangrayson

939620c

Commit History

Feb 20, 2025

Adding `safetensors` variant of this model⁠

Apr 5, 2023

Training done (#3)⁠

Training done (#2)⁠

Training in progress, epoch 0 (#1)⁠

initial commit