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

Libraries

How to use vivek-pathania/donut-base-sroie with Transformers:

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

pipe = pipeline("image-text-to-text", model="vivek-pathania/donut-base-sroie")

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

tokenizer = AutoTokenizer.from_pretrained("vivek-pathania/donut-base-sroie")
model = AutoModelForMultimodalLM.from_pretrained("vivek-pathania/donut-base-sroie", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use vivek-pathania/donut-base-sroie with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/vivek-pathania/donut-base-sroie

SGLang

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

Docker Model Runner
How to use vivek-pathania/donut-base-sroie with Docker Model Runner:
```
docker model run hf.co/vivek-pathania/donut-base-sroie
```

donut-base-sroie

This model is a fine-tuned version of naver-clova-ix/donut-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.7974

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 4
eval_batch_size: 16
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.1933	1.0	24	0.9206
0.2084	2.0	48	0.8872
0.1692	3.0	72	0.8975
0.1341	4.0	96	0.8255
0.1333	5.0	120	0.8524
0.1217	6.0	144	0.8312
0.1132	7.0	168	0.8814
0.0767	8.0	192	0.8282
0.0798	9.0	216	0.8331
0.0939	10.0	240	0.9095
0.0736	11.0	264	0.8566
0.0733	12.0	288	0.7841
0.0351	13.0	312	0.8250
0.0571	14.0	336	0.8270
0.0398	15.0	360	0.7958
0.0383	16.0	384	0.8322
0.0282	17.0	408	0.8043
0.0375	18.0	432	0.8077
0.0392	19.0	456	0.7974
0.047	20.0	480	0.7974

Framework versions

Transformers 4.57.1
Pytorch 2.8.0+cu126
Datasets 4.4.1
Tokenizers 0.22.1

Downloads last month: 17

Safetensors

Model size

0.2B params

Tensor type

I64

F32

Model tree for vivek-pathania/donut-base-sroie

Base model

naver-clova-ix/donut-base

Finetuned

(487)

this model