Update README.md

README.md

@@ -116,7 +116,7 @@ for r in res:
 **Evaluation:**
 
 Granite-Embedding-30m-Sparse is competive in performance to the naver/splade-v3-distilbert despite being half the parameter size. We also compare the sparse model with similar sized dense embedding counterpart `ibm-granite/granite-embedding-30m-english`. The performance of the models on MTEB Retrieval (i.e., BEIR) is reported below. 
-To maintain consistency with results reported by `naver/splade-v3-distilbert`, we do not include CQADupstack and MS-MARCO int he table below.
+To maintain consistency with results reported by `naver/splade-v3-distilbert`, we do not include CQADupstack and MS-MARCO in the table below.
 
 | Model                           | Paramters (M)| Vocab Size |  BEIR Retrieval (13) |
 |---------------------------------|:------------:|:-------------------:|:-------------------: |