Update README.md

README.md

@@ -76,24 +76,6 @@ The model is trained using the MatryoshkaLoss for embeddings of size 1024, 786,
 - **Maximum Sequence Length:** 512 tokens
 - **Output Dimensionality:** 1024 tokens
 - **Similarity Function:** Cosine Similarity
-<!-- - **Training Dataset:** Unknown -->
-<!-- - **Language:** Unknown -->
-<!-- - **License:** Unknown -->
-
-### Model Sources
-
-- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
-- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
-- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
-
-### Full Model Architecture
-
-```
-SentenceTransformer(
-  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: XLMRobertaModel 
-  (1): Pooling({'word_embedding_dimension': 1024, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
-)
-```
 
 ## Usage
 
@@ -114,9 +96,9 @@ matryoshka_dim = 786
 model = SentenceTransformer("omarelshehy/Arabic-STS-Matryoshka", truncate_dim=matryoshka_dim)
 # Run inference
 sentences = [
-    'سوق للمنتجات داخل مبنى كبير ذو جدران بيضاء.',
-    'السوق يبيع الخضروات.',
-    'سوق المنتجات داخل مبنى صغير أسود الجدران.',
+    'أحب قراءة الكتب في أوقات فراغي.',
+    'أستمتع بقراءة القصص في المساء قبل النوم.',
+    'القراءة تعزز معرفتي وتفتح أمامي آفاق جديدة.',
 ]
 embeddings = model.encode(sentences)
 print(embeddings.shape)
@@ -128,30 +110,6 @@ print(similarities.shape)
 # [3, 3]
 ```
 
-<!--
-### Direct Usage (Transformers)
-
-<details><summary>Click to see the direct usage in Transformers</summary>
-
-</details>
--->
-
-<!--
-### Downstream Usage (Sentence Transformers)
-
-You can finetune this model on your own dataset.
-
-<details><summary>Click to expand</summary>
-
-</details>
--->
-
-<!--
-### Out-of-Scope Use
-
-*List how the model may foreseeably be misused and address what users ought not to do with the model.*
--->
-
 ## Evaluation
 
 ### Metrics