add model

app.py

@@ -38,7 +38,7 @@ def load_model():
     pretrained_model_name = "kykim/bert-kor-base"
 
     tokenizer = BertTokenizerFast.from_pretrained(pretrained_model_name)
-    model = AutoModel.from_pretrained(pretrained_model_name)
+    model = AutoModel.from_pretrained("./bertmodel/")
 
     return model, tokenizer
 

bertmodel/config.json

@@ -0,0 +1,33 @@
+{
+  "_name_or_path": "kykim/bert-kor-base",
+  "architectures": [
+    "BertModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "directionality": "bidi",
+  "embedding_size": 768,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "pooler_fc_size": 768,
+  "pooler_num_attention_heads": 12,
+  "pooler_num_fc_layers": 3,
+  "pooler_size_per_head": 128,
+  "pooler_type": "first_token_transform",
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.12.5",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 42000
+}

bertmodel/pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9a1600914f64f627a2fa12ceaf46c16f8626ec8b91f9802e00de5c184fcdfdc1
+size 473267953