Instructions to use cyttic/trocr-ara-fonts64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use cyttic/trocr-ara-fonts64 with Transformers:

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

pipe = pipeline("image-text-to-text", model="cyttic/trocr-ara-fonts64")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("cyttic/trocr-ara-fonts64")
model = AutoModelForMultimodalLM.from_pretrained("cyttic/trocr-ara-fonts64", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use cyttic/trocr-ara-fonts64 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cyttic/trocr-ara-fonts64"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cyttic/trocr-ara-fonts64",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/cyttic/trocr-ara-fonts64

SGLang

How to use cyttic/trocr-ara-fonts64 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 "cyttic/trocr-ara-fonts64" \
    --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": "cyttic/trocr-ara-fonts64",
		"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 "cyttic/trocr-ara-fonts64" \
        --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": "cyttic/trocr-ara-fonts64",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use cyttic/trocr-ara-fonts64 with Docker Model Runner:
```
docker model run hf.co/cyttic/trocr-ara-fonts64
```

trocr-ara-fonts64

This model is a fine-tuned version of cyttic/hatformer-synthetic-arabic on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.0265
Cer: 0.0006

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: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 16
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
lr_scheduler_warmup_steps: 0.1
training_steps: 4000

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
0.2364	0.0161	250	0.0717	0.0034
0.2522	0.0323	500	0.0785	0.0034
0.1697	0.0484	750	0.0696	0.0033
0.1362	0.0645	1000	0.0782	0.0044
0.1461	0.0806	1250	0.0586	0.0021
0.1376	0.0968	1500	0.0537	0.0016
0.1009	0.1129	1750	0.0551	0.0017
0.1136	0.1290	2000	0.0467	0.0015
0.1697	0.1452	2250	0.0537	0.0099
0.0766	0.1613	2500	0.0370	0.0010
0.0890	0.1774	2750	0.0337	0.0007
0.0805	0.1935	3000	0.0312	0.0009
0.0539	0.2097	3250	0.0299	0.0007
0.0677	0.2258	3500	0.0280	0.0006
0.0694	0.2419	3750	0.0270	0.0007
0.0591	0.2581	4000	0.0265	0.0006

Framework versions

Transformers 5.14.1
Pytorch 2.11.0+cu128
Datasets 5.0.1
Tokenizers 0.22.2

Downloads last month: 12

Safetensors

Model size

0.3B params

Tensor type

F32

Inference Providers NEW

Image-Text-to-Text

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Model tree for cyttic/trocr-ara-fonts64

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cyttic/hatformer-synthetic-arabic

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