Image-to-Text
Transformers
Safetensors
Tibetan
vision-encoder-decoder
image-text-to-text
ocr
tibetan
document-ai
trocr
Instructions to use TibetanCodexAITeam/PechaBridgeOCR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TibetanCodexAITeam/PechaBridgeOCR 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="TibetanCodexAITeam/PechaBridgeOCR")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("TibetanCodexAITeam/PechaBridgeOCR") model = AutoModelForMultimodalLM.from_pretrained("TibetanCodexAITeam/PechaBridgeOCR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload DONUT checkpoint checkpoint-154000 via PechaBridge
Browse files- repro/cer_step_154000.json +13 -0
repro/cer_step_154000.json
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{
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"step": 154000,
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"checkpoint_dir": "/home/ubuntu/data/PechaBridge/models/donut_full_gray_aug_restart/checkpoint-154000",
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"repro_cer": 0.027263326125787347,
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"repro_cer_percent": 2.7263326125787346,
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"repro_valid_n": 300,
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"repro_empty_ref_count": 0,
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"repro_empty_pred_count": 0,
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"repro_edit_sum": 1160,
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"repro_ref_len_sum": 42548,
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"repro_runtime": 41.041670083999634,
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"repro_world_size": 1
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}
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