Update README.md

README.md

@@ -18,6 +18,12 @@ tags:
 Implemented the [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
 ](https://arxiv.org/abs/1910.13461) paper from scratch using `PyTorch` for an abstractive summarization task in Arabic.
 
+>[!IMPORTANT]
+> The model inferenc is not ready, i mean you can't loading it directly from the `Transformers` library.
+>
+> As soon as possible i will create an inference API, and integrate the model with the Transformers library.
+>
+
 ## Goal
 
 Reproduce the BART model from scratch to understand its architecture in depth, using the minimum available resources.
@@ -41,8 +47,6 @@ The dataset used is the [XL-Sum(Arabic Subset)](https://github.com/csebuetnlp/xl
   - validation: `4689 rows`.
   - test: `4689 rows`.
 
-## Summary
-
 ## Results
 
 | Epoch | Loss(train) | Loss(validation) | Epoch Time (hours) | Training Time (hours) |  Device  |
@@ -54,13 +58,6 @@ The dataset used is the [XL-Sum(Arabic Subset)](https://github.com/csebuetnlp/xl
 |   5   |    9.01     |       8.92       |        0.22        |          1.1          | 1 x L4OS |
 
 
-
-## Usage
-
-```python
-
-```
-
 ## License
 
 This model is licensed under the `MIT` License.