Update README.md

README.md

@@ -22,7 +22,9 @@ You can learn more about the models in our [blog post](https://www.mixedbread.ai
 
 We recommend using the [RAGatouille](https://github.com/bclavie/RAGatouille) for using our ColBERT model.
 
-`pip install ragatouille`
+```sh
+pip install ragatouille
+```
 
 
 
@@ -52,17 +54,23 @@ results = RAG.search(query)
 The result looks like this:
 
 ```
-[{'content': "'To Kill a Mockingbird' is a novel by Harper Lee published in 1960. It was immediately successful, winning the Pulitzer Prize, and has become a classic of modern American literature.",
-  'score': 28.453125,
-  'rank': 1,
-  'document_id': '9d564e82-f14f-433a-ab40-b10bda9dc370',
-  'passage_id': 0},
- {'content': "Harper Lee, an American novelist widely known for her novel 'To Kill a Mockingbird', was born in 1926 in Monroeville, Alabama. She received the Pulitzer Prize for Fiction in 1961.",
-  'score': 27.03125,
-  'rank': 2,
-  'document_id': 'a35a89c3-b610-4e2e-863e-fa1e7e0710a6',
-  'passage_id': 2},
-  ...]
+[
+  {
+    'content': "'To Kill a Mockingbird' is a novel by Harper Lee published in 1960. It was immediately successful, winning the Pulitzer Prize, and has become a classic of modern American literature.",
+    'score': 28.453125,
+    'rank': 1,
+    'document_id': '9d564e82-f14f-433a-ab40-b10bda9dc370',
+    'passage_id': 0
+  },
+ {
+    'content': "Harper Lee, an American novelist widely known for her novel 'To Kill a Mockingbird', was born in 1926 in Monroeville, Alabama. She received the Pulitzer Prize for Fiction in 1961.",
+    'score': 27.03125,
+    'rank': 2,
+    'document_id': 'a35a89c3-b610-4e2e-863e-fa1e7e0710a6',
+    'passage_id': 2
+  },
+  ...
+]
 ```
 
 ## Using API
@@ -99,7 +107,7 @@ Find more in our [blog-post](https://www.mixedbread.ai/blog/mxbai-rerank-v1) and
 
 ### 2. Retrieval Performance
 
-ColBERT is mainly used for reranking. Here, we also test our model's performance on retrieval tasks on a subset of the BEIR benchmarks.
+We also test our model's performance on retrieval tasks on a subset of the BEIR benchmarks. We'll be providing the full results for the benchmark soon (actively working on it).
 
 Due to resource limitations, we only test our model on three beir tasks. NDCG@10 servers as the main metric. 
 
@@ -110,7 +118,7 @@ Due to resource limitations, we only test our model on three beir tasks. NDCG@10
 | SciFact    |      68.9 |            70.1 |               **71.3** |
 | TREC-COVID |      72.6 |            75.0 |               **80.5** |
 
-Although our ColBERT also performs well on retrieval, we recommend using our embedding model [mixedbread-ai/mxbai-embed-large-v1](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1) for retrieval.
+Although our ColBERT also performs well on retrieval tasks, we still recommend using our flagship embedding model [mixedbread-ai/mxbai-embed-large-v1](https://huggingface.co/mixedbread-ai/mxbai-embed-large-v1) for that.
 
 
 ## Community