Add library_name and pipeline_tag tags

This PR ensures a button will appear regarding "how to use" at the top right.

README.md

@@ -1,11 +1,14 @@
 ---
 license: cc-by-nc-4.0
+library_name: sentence-transformers
+pipeline_tag: feature-extraction
 ---
+
 <h1 align="center">Salesforce/SFR-Embedding-Code-2B_R</h1>
 
 **SFR-Embedding by Salesforce Research.**
 
-The Salesforce/SFR-Embedding-Code is a generalist embedding model family for multilingual and multi-task code and Text retrieval. It demonstrates superior performance compared to various open-source code embedding models across multiple code retrieval tasks.
+This model is based on the model described in the paper [CodeXEmbed: A Generalist Embedding Model Family for Multiligual and Multi-task Code Retrieval](https://huggingface.co/papers/2411.12644). It is a generalist embedding model family for multilingual and multi-task code and Text retrieval. It demonstrates superior performance compared to various open-source code embedding models across multiple code retrieval tasks.
 
 Check out our [paper](https://arxiv.org/abs/2411.12644) for more details!
 
@@ -76,6 +79,24 @@ scores = (query_embeddings @ passage_embeddings.T) * 100
 print(scores.tolist())
 ```
 
+#### Sentence Transformers
+
+# Requires sentence_transformers>=2.7.0
+```python
+from sentence_transformers import SentenceTransformer
+from sentence_transformers.util import cos_sim
+
+sentences = [
+    "how to implement quick sort in Python?",
+    "def quick_sort(arr):\n    if len(arr) <= 1:\n        return arr\n    pivot = arr[len(arr) // 2]\n    left = [x for x in arr if x < pivot]\n    middle = [x for x in arr if x == pivot]\n    right = [x for x in arr if x > pivot]\n    return quick_sort(left) + middle + quick_sort(right)",
+    "def bubble_sort(arr):\n    n = len(arr)\n    for i in range(n):\n        for j in range(0, n-i-1):\n            if arr[j] > arr[j+1]:\n                arr[j], arr[j+1] = arr[j+1], arr[j]\n    return arr",
+]
+
+model = SentenceTransformer('Salesforce/SFR-Embedding-Code-2B_R', trust_remote_code=True)
+embeddings = model.encode(sentences)
+print(cos_sim(embeddings[0], embeddings[1:]))
+```
+
 ### Citation
 ```bibtex
 @article{liu2024codexembed,
@@ -84,5 +105,4 @@ print(scores.tolist())
   journal={arXiv preprint arXiv:2411.12644},
   year={2024}
 }
-```
-
+```