docs(readme): update python examples to reference correct model name

README.md

@@ -64,8 +64,8 @@ input_texts = [
     "sorting algorithms"
 ]
 
-tokenizer = AutoTokenizer.from_pretrained("thenlper/gte-small")
-model = AutoModel.from_pretrained("thenlper/gte-small")
+tokenizer = AutoTokenizer.from_pretrained("Supabase/gte-small")
+model = AutoModel.from_pretrained("Supabase/gte-small")
 
 # Tokenize the input texts
 batch_dict = tokenizer(input_texts, max_length=512, padding=True, truncation=True, return_tensors='pt')
@@ -86,7 +86,7 @@ from sentence_transformers.util import cos_sim
 
 sentences = ['That is a happy person', 'That is a very happy person']
 
-model = SentenceTransformer('thenlper/gte-large')
+model = SentenceTransformer('Supabase/gte-small')
 embeddings = model.encode(sentences)
 print(cos_sim(embeddings[0], embeddings[1]))
 ```