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
Download sentencepiece.bpe.model from acceler-technology/dev-lhdn-parse-donut-model: direct link, hf CLI and curl.
- Browser
- Download file 1.3 MB
-
https://huggingface.co/acceler-technology/dev-lhdn-parse-donut-model/resolve/main/sentencepiece.bpe.model
- Command line
-
hf download hf://acceler-technology/dev-lhdn-parse-donut-model/sentencepiece.bpe.model
-
curl -L -o sentencepiece.bpe.model https://huggingface.co/acceler-technology/dev-lhdn-parse-donut-model/resolve/main/sentencepiece.bpe.model
1.3 MB
- Xet hash:
- f85a83334151f5857186c12f60176b2f0f186620886e5ea4265fdb27fbb6de09
- Size of remote file:
- 1.3 MB
- SHA256:
- cb9e3dce4c326195d08fc3dd0f7e2eee1da8595c847bf4c1a9c78b7a82d47e2d
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