Instructions to use microsoft/trocr-large-printed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/trocr-large-printed 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="microsoft/trocr-large-printed")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("microsoft/trocr-large-printed") model = AutoModelForMultimodalLM.from_pretrained("microsoft/trocr-large-printed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Update preprocessor_config.json
Verified signatureUpdate preprocessor type.72e7767
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Adding `safetensors` variant of this model (#3)
- Adding `safetensors` variant of this model (db0356248cdfcd23511c50c25418aa78a1c30255) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>b2a847a
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Adding generation config file(s)
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Update README.md (#1)
- Update README.md (bb29a6f8430e092541b21b3a122c2a332cc476ad) Co-authored-by: Loïck BOURDOIS <lbourdois@users.noreply.huggingface.co>e0ab580
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Rename encoder_hidden_size to cross_attention_hidden_size
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initial commit
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