Instructions to use microsoft/table-transformer-detection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/table-transformer-detection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="microsoft/table-transformer-detection")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("microsoft/table-transformer-detection") model = AutoModelForObjectDetection.from_pretrained("microsoft/table-transformer-detection") - Notebooks
- Google Colab
- Kaggle
Hyperparameter tuning of table transformer
#5
by andreashrb - opened
I am currently implementing the Table Transformer and would like to further improve the model fine tuned to my data.
Is there a possibility to tune hyperparameters? If so, which ones are particularly relevant here?
Unfortunately, there is very little information about hyperparameter tuning around DETR, many publications only refer to BERT. Can mentioned BERT information be used also in DETR?
Thanks and have a nice day.
hi there ,
did you find any solution about tuning the hyperparameters ?
thanks in advance .