Instructions to use Tamazight/Tifinagh-Nougat-Small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Tamazight/Tifinagh-Nougat-Small with Transformers:

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

pipe = pipeline("image-text-to-text", model="Tamazight/Tifinagh-Nougat-Small")

# Load model directly
from transformers import AutoTokenizer, AutoModelForImageTextToText

tokenizer = AutoTokenizer.from_pretrained("Tamazight/Tifinagh-Nougat-Small")
model = AutoModelForImageTextToText.from_pretrained("Tamazight/Tifinagh-Nougat-Small")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use Tamazight/Tifinagh-Nougat-Small with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Tamazight/Tifinagh-Nougat-Small

SGLang

How to use Tamazight/Tifinagh-Nougat-Small 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 "Tamazight/Tifinagh-Nougat-Small" \
    --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": "Tamazight/Tifinagh-Nougat-Small",
		"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 "Tamazight/Tifinagh-Nougat-Small" \
        --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": "Tamazight/Tifinagh-Nougat-Small",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Tamazight/Tifinagh-Nougat-Small with Docker Model Runner:
```
docker model run hf.co/Tamazight/Tifinagh-Nougat-Small
```

Tifinagh-Nougat-Small

File size: 593 Bytes

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{
  "image_processor": {
    "data_format": "channels_first",
    "do_align_long_axis": false,
    "do_crop_margin": false,
    "do_normalize": true,
    "do_pad": true,
    "do_rescale": true,
    "do_resize": true,
    "do_thumbnail": false,
    "image_mean": [
      0.485,
      0.456,
      0.406
    ],
    "image_processor_type": "NougatImageProcessor",
    "image_std": [
      0.229,
      0.224,
      0.225
    ],
    "resample": 2,
    "rescale_factor": 0.00392156862745098,
    "size": {
      "height": 896,
      "width": 672
    }
  },
  "processor_class": "NougatProcessor"
}