Instructions to use Superd4/lasttest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Superd4/lasttest 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="Superd4/lasttest")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("Superd4/lasttest") model = AutoModelForMultimodalLM.from_pretrained("Superd4/lasttest", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| language: ja | |
| tags: | |
| - image-to-text | |
| license: apache-2.0 | |
| datasets: | |
| - manga109s | |
| # Manga OCR | |
| Optical character recognition for Japanese text, with the main focus being Japanese manga. | |
| It uses [Vision Encoder Decoder](https://huggingface.co/docs/transformers/model_doc/vision-encoder-decoder) framework. | |
| Manga OCR can be used as a general purpose printed Japanese OCR, but its main goal was to provide a high quality | |
| text recognition, robust against various scenarios specific to manga: | |
| - both vertical and horizontal text | |
| - text with furigana | |
| - text overlaid on images | |
| - wide variety of fonts and font styles | |
| - low quality images | |
| Code is available [here](https://github.com/kha-white/manga_ocr). | |