WalidHadri-Iron

@Ashwani-Dangwal To get the logits using HF model, it is in the output of the model, you can have it using `model(**encoding).logits` Could this problem be coming from the pre-processing...

> Hi, > > I am attaching the training parameters I used & the command I used to train (All from table-transformers original repo): > > ``` > { >...

@Prabhav55 If you did the conversion, I loaded the model using `TableTransformerForObjectDetection.from_pretrained(model_folder_path)` Where basically the model_folder_path is the path to the folder where you put the three files you got...

@thiagodma For the dataset preparation, I wonder on what dataset you fine-tuned it. If you did on FinTabNet, did you use the code here to canonize the cells and get...

@giuqoob I just fine-tuned on FinTabNet, I kept the configuration the same for TSR, except the learning rates that I changed: from `"lr":5e-5,"lr_backbone":1e-5` to `"lr":1e-5, "lr_backbone":1e-6`. I fine-tuned for 15...

> Hi, > > Recently I have tried fine-tuning the table transformer model with a small dataset. However, I was wondering if there is a way to load the model...

> @WalidHadri-Iron @giuqoob Available FinTabNet Dataset [here](https://developer.ibm.com/exchanges/data/all/fintabnet/) Can be processed to match the new paper using code from this repo, would it be hard to point to these folders? >...

@Ashwani-Dangwal I did exactly like @Prabhav55

@hyshandler I guess either you use the implementation in this repo directly, because you have all the post-processing steps available until the construction of the dataframe, or you combine the...

@hyshandler the post-processing code is here https://github.com/microsoft/table-transformer/blob/main/src/postprocess.py and the steps are grouped here https://github.com/microsoft/table-transformer/blob/main/src/inference.py . What you have in "results" is a bunch of bounding boxes with labels and scores,...