Merge pull request #21 from MinishLab/update-model-list

docs: Added multilingual model

Author: stephantul

README.md

@@ -36,7 +36,7 @@ model_name = "minishlab/M2V_base_output"
 model = StaticModel.from_pretrained(model_name)
 
 # Make embeddings
-embeddings = model.encode(["It's dangerous to go alone!", "It's a secret to everyone."])
+embeddings = model.encode(["It's dangerous to go alone!", "It's a secret to everybody."])
 ```
 
 And that's it. You can use the model to classify texts, to cluster, or to build a RAG system.
@@ -185,6 +185,7 @@ print(make_leaderboard(task_scores))
 |------------------------|-------------|-----------------------------------------------------------------------|----------------|-----------------------|--------------|
 | [M2V_base_glove](https://huggingface.co/minishlab/M2V_base_glove)           | English     | Flagship embedding model based on GloVe vocab.           | GloVe        | [bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5)                   | 102M         |
 | [M2V_base_output](https://huggingface.co/minishlab/M2V_base_output)          | English     | Flagship embedding model based on bge-base-en-v1.5 vocab. Uses a subword tokenizer.                    | Output          | [bge-base-en-v1.5](https://huggingface.co/BAAI/bge-base-en-v1.5)                         | 7.5M         |
+| [M2V_multilingual_output](https://huggingface.co/minishlab/M2V_multilingual_output)          | Multilingual     | Flagship multilingual embedding model based on LaBSE vocab. Uses a subword tokenizer.                    | Output          | [LaBSE](https://huggingface.co/sentence-transformers/LaBSE)                         | 471M         |
 ## Results
 
 ### Main Results