feat: new model

main.py

@@ -24,8 +24,8 @@ def mean_pooling(model_output, attention_mask):
     return torch.sum(token_embeddings * input_mask_expanded, 1) / torch.clamp(input_mask_expanded.sum(1), min=1e-9)
 
 
-tokenizer = AutoTokenizer.from_pretrained('sentence-transformers/all-MiniLM-L6-v2')
-model = AutoModel.from_pretrained('sentence-transformers/all-MiniLM-L6-v2')
+tokenizer = AutoTokenizer.from_pretrained('models/all-MiniLM-L6-v2')
+model = AutoModel.from_pretrained('models/all-MiniLM-L6-v2')
 
 app = FastAPI()
 

models/all-MiniLM-L6-v2

@@ -0,0 +1 @@
+Subproject commit 7dbbc90392e2f80f3d3c277d6e90027e55de9125