Update README.md

README.md

@@ -1,7 +1,8 @@
-
 ---
 pipeline_tag: sentence-similarity
-language: fr
+language:
+- fr
+- en
 license: apache-2.0
 tags:
 - passage-retrieval
@@ -14,11 +15,11 @@ base_model_relation: quantized
 # 🇫🇷 french-gte-multilingual-base
 
 This model is a 51.4% smaller version of [Alibaba-NLP/gte-multilingual-base](https://huggingface.co/Alibaba-NLP/gte-multilingual-base) 
-for the French language, created using the [mtem-pruner](https://huggingface.co/spaces/antoinelouis/mtem-pruner) space.
+for the French and English language, created using the [mtem-pruner](https://huggingface.co/spaces/antoinelouis/mtem-pruner) space.
 
-This pruned model should perform similarly to the original model for French language tasks with a much smaller 
+This pruned model should perform similarly to the original model for French and English language tasks with a much smaller 
 memory footprint. However, it may not perform well for other languages present in the original multilingual model as tokens not 
-commonly used in French were removed from the original multilingual model's vocabulary.
+commonly used in French and English were removed from the original multilingual model's vocabulary.
 
 ## Usage
 
@@ -27,7 +28,7 @@ You can use this model with the Transformers library:
 ```python
 from transformers import AutoModel, AutoTokenizer
 
-model_name = "ijohn07/french-gte-multilingual-base"
+model_name = "ijohn07/french-english-gte-base"
 model = AutoModel.from_pretrained(model_name, trust_remote_code=True)
 tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True, use_fast=True)
 ```
@@ -37,7 +38,7 @@ Or with the sentence-transformers library:
 ```python
 from sentence_transformers import SentenceTransformer
 
-model = SentenceTransformer("ijohn07/french-gte-multilingual-base")
+model = SentenceTransformer("ijohn07/french-english-gte-base")
 ```
 
-**Credits**: cc [@antoinelouis](https://huggingface.co/antoinelouis)
+**Credits**: cc [@antoinelouis](https://huggingface.co/antoinelouis)