Update README.md

README.md

@@ -1,20 +1,20 @@
 ---
-pipeline_tag: fill-mask
+pipeline_tag: sentence-similarity
 language: nld
 license: mit
 tags:
-  - trimmed
-library_name: transformers
+- trimmed
+library_name: sentence-transformers
 base_model: intfloat/multilingual-e5-base
 base_model_relation: quantized
 datasets:
-  - Lumberjackk/fineweb-2-trimming
+- Lumberjackk/fineweb-2-trimming
 ---
 
 # multilingual-e5-base-nld-32768
 
 This model is a 60.0% smaller version of [intfloat/multilingual-e5-base](https://huggingface.co/intfloat/multilingual-e5-base) 
-optimized for multiple languages with vocabulary pruning.
+optimized for Dutch language via vocabulary pruning.
 
 **Total vocabulary size**: 32768 tokens (reduced from 250002)  
 **Tokenizer type**: Unigram  
@@ -25,18 +25,14 @@ optimized for multiple languages with vocabulary pruning.
 
 - **nld**: 32768 tokens
 
-This pruned model should perform similarly to the original model for the selected languages with a much smaller 
+This pruned model should perform similarly to the original model for Dutch with a much smaller 
 memory footprint. However, it may not perform well for other languages as tokens not commonly used in the selected 
 languages were removed from the vocabulary.
 
 ## Usage
 
-You can use this model with the Transformers library:
+You can use this model with the SentenceTransformer library:
 ```python
-from transformers import AutoModel, AutoTokenizer
-
-model_name = "Lumberjackk/multilingual-e5-base-nld-32768"
-model = AutoModel.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-```
-        
+from sentence_transformers import SentenceTransformer
+model = SentenceTransformer("Lumberjackk/multilingual-e5-base-nld-32768")
+```