Image-to-Text
Transformers
Safetensors
vision-encoder-decoder
image-text-to-text
donut
document-parsing
lhdn
ebc
Instructions to use acceler-technology/dev-lhdn-parse-donut-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use acceler-technology/dev-lhdn-parse-donut-model 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="acceler-technology/dev-lhdn-parse-donut-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("acceler-technology/dev-lhdn-parse-donut-model") model = AutoModelForMultimodalLM.from_pretrained("acceler-technology/dev-lhdn-parse-donut-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- config.json +1 -1
config.json
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{
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"_name_or_path": "
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"architectures": [
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"VisionEncoderDecoderModel"
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],
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{
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"_name_or_path": "kwyong/ebc-donut-finetuned",
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"architectures": [
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"VisionEncoderDecoderModel"
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],
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