Update README.md

README.md

@@ -46,7 +46,7 @@ Then you can use the model like this:
 from sentence_transformers import SentenceTransformer
 sentences = ["Apprendre le python", "Devenir expert en comptabilité"]
 
-model = SentenceTransformer('inokufu/bertheo')
+model = SentenceTransformer('inokufu/flaubert-base-uncased-xnli-sts-finetuned-education')
 embeddings = model.encode(sentences)
 print(embeddings)
 ```
@@ -72,8 +72,8 @@ def mean_pooling(model_output, attention_mask):
 sentences = ["Apprendre le python", "Devenir expert en comptabilité"]
 
 # Load model from HuggingFace Hub
-tokenizer = AutoTokenizer.from_pretrained('inokufu/bertheo')
-model = AutoModel.from_pretrained('inokufu/bertheo')
+tokenizer = AutoTokenizer.from_pretrained('inokufu/flaubert-base-uncased-xnli-sts-finetuned-education')
+model = AutoModel.from_pretrained('inokufu/flaubert-base-uncased-xnli-sts-finetuned-education')
 
 # Tokenize sentences
 encoded_input = tokenizer(sentences, padding=True, truncation=True, return_tensors='pt')