Instructions to use SalML/DETR-table-structure-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SalML/DETR-table-structure-recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="SalML/DETR-table-structure-recognition")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("SalML/DETR-table-structure-recognition") model = AutoModelForObjectDetection.from_pretrained("SalML/DETR-table-structure-recognition") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -6,6 +6,6 @@ license: unknown
|
|
| 6 |
datasets:
|
| 7 |
- PubTables-1M
|
| 8 |
---
|
| 9 |
-
# The models are taken from
|
| 10 |
I have built a HuggingFace Space: https://huggingface.co/spaces/SalML/TableTransformer2CSV
|
| 11 |
It runs an OCR on the table-transformer output image to obtain a CSV downloadable table.
|
|
|
|
| 6 |
datasets:
|
| 7 |
- PubTables-1M
|
| 8 |
---
|
| 9 |
+
# The models are taken from https://github.com/microsoft/table-transformer/
|
| 10 |
I have built a HuggingFace Space: https://huggingface.co/spaces/SalML/TableTransformer2CSV
|
| 11 |
It runs an OCR on the table-transformer output image to obtain a CSV downloadable table.
|