Update README.md

README.md

@@ -8,8 +8,6 @@ tags:
  
 # Model Details
  
-## Model Description
- 
 detr-doc-table-detection is a model trained to detect both **Bordered** and **Borderless** tables in documents, based on [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50).
  
 - **Developed by:** Taha Douaji
@@ -30,10 +28,6 @@ detr-doc-table-detection is a model trained to detect both **Bordered** and **Bo
 ## Direct Use
 This model can be used for the task of object detection.
  
-## Downstream Use [Optional]
- 
-More information needed.
- 
 ## Out-of-Scope Use
  
 The model should not be used to intentionally create hostile or alienating environments for people. 
@@ -59,14 +53,6 @@ The model was trained on ICDAR2019 Table Dataset
 ## Training Procedure
 
  
-### Preprocessing
- 
-More information needed 
- 
-### Speeds, Sizes, Times
-More information needed 
-
- 
 # Evaluation
  
  
@@ -172,9 +158,7 @@ More information needed
 # How to Get Started with the Model
  
 Use the code below to get started with the model.
- 
-<details>
-<summary> Click to expand </summary>
+
 
 ```python
 from transformers import DetrImageProcessor, DetrForObjectDetection
@@ -202,5 +186,4 @@ for score, label, box in zip(results["scores"], results["labels"], results["boxe
             f"Detected {model.config.id2label[label.item()]} with confidence "
             f"{round(score.item(), 3)} at location {box}"
     )
-```
-</details>
+```