Image-to-Text
Transformers
Safetensors
Turkish
lighton_ocr
image-text-to-text
ocr
document-understanding
turkish
enterprise
vision-language
werea
Instructions to use GoktugD/Werea-DocOCR-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GoktugD/Werea-DocOCR-1B with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="GoktugD/Werea-DocOCR-1B")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("GoktugD/Werea-DocOCR-1B") model = AutoModelForMultimodalLM.from_pretrained("GoktugD/Werea-DocOCR-1B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "image_processor": { | |
| "data_format": "channels_first", | |
| "default_to_square": true, | |
| "do_convert_rgb": true, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.48145466, | |
| 0.4578275, | |
| 0.40821073 | |
| ], | |
| "image_processor_type": "PixtralImageProcessor", | |
| "image_std": [ | |
| 0.26862954, | |
| 0.26130258, | |
| 0.27577711 | |
| ], | |
| "patch_size": 14, | |
| "resample": 3, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "longest_edge": 1540 | |
| } | |
| }, | |
| "patch_size": 14, | |
| "processor_class": "LightOnOcrProcessor", | |
| "spatial_merge_size": 2 | |
| } | |