Image-to-Text
Transformers
ONNX
vision-encoder-decoder
image-text-to-text
latex-ocr
math-ocr
math-formula-recognition
mfr
pix2text
p2t
Instructions to use breezedeus/pix2text-mfr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use breezedeus/pix2text-mfr 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="breezedeus/pix2text-mfr")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("breezedeus/pix2text-mfr") model = AutoModelForMultimodalLM.from_pretrained("breezedeus/pix2text-mfr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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print(merge_line_texts(outs2))
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```
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## Performance / 性能
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print(merge_line_texts(outs2))
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```
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### Method 3: Notebook
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Just try Pix2Text with this notebook: [https://github.com/breezedeus/Pix2Text/blob/main/pix2text_v1_0.ipynb](https://github.com/breezedeus/Pix2Text/blob/main/pix2text_v1_0.ipynb).
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## Performance / 性能
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