Comments (2)
Why not? However, It's better to keep your batch prompt in the same length when inferring.
from donut.
Why not? However, It's better to keep your batch prompt in the same length when inferring.
thanks
from donut.
Related Issues (20)
- getting no module named lightning module when trying to run the fine tuning code in train.py file of donut model. HOT 1
- DOCVQA data set format ? HOT 3
- Prediction and Answer differ by dataset-specific tag HOT 1
- The latest update has the model weights twice the embedding dim size of the actual model installed through github or pip HOT 2
- VisionEncoderDecoderModel convert HOT 2
- Integrate a customized internal OCR engine to Donut HOT 1
- Request: Dataset and pretrained model for language detection
- Problem with getting predictions HOT 7
- Does synthdog data has MiT or afl-3.0 license? HOT 1
- Error "A configuraton of type donut cannot be instantiated because not both `encoder` and `decoder` sub-configurations are passed" when run inference after finetuned docvqa without pushing to hugging face?
- custom json schema - ASAP HOT 2
- Multi GPU support for fine tuning
- How to extract complete text from the document? HOT 3
- confidence 값의 공식적인 지원
- Classification inference
- Update donut-python Python Package to be compatible with latest versions of transformers
- donut inference시 sub task가 변경?
- Not getting prediction correctly using the model trained on the custom dataset (similar format as CORD-V2 dataset)
- not work this app.py
- Can synthdog insert text for a specified bbox? HOT 1
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