Update README.md

README.md

@@ -374,8 +374,8 @@ import torch
 from transformers import AutoModelForSequenceClassification, AutoTokenizer
 
 tokenizer = AutoTokenizer.from_pretrained('BAAI/bge-reranker-large')
-model = AutoModelForSequenceClassification.from_pretrained('BAAI/bge-reranker-large')
-model_ort = ORTModelForFeatureExtraction.from_pretrained('BAAI/bge-reranker-large', file_name="onnx/model.onnx")
+model = AutoModelForSequenceClassification.from_pretrained('BAAI/bge-reranker-base')
+model_ort = ORTModelForSequenceClassification.from_pretrained('BAAI/bge-reranker-base', file_name="onnx/model.onnx")
 
 # Sentences we want sentence embeddings for
 pairs = [['what is panda?', 'hi'], ['what is panda?', 'The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China.']]
@@ -401,7 +401,7 @@ query='what is panda?'
 docs = ['The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear', "Paris is in France."]
 
 engine = AsyncEmbeddingEngine.from_args(
-    EngineArgs(model_name_or_path = "BAAI/bge-large-en-v1.5", device="cpu", engine="optimum" # or engine="torch"
+    EngineArgs(model_name_or_path = "BAAI/bge-reranker-base", device="cpu", engine="optimum" # or engine="torch"
 ))
 
 async def main():