update model

README.md

@@ -1,11 +1,14 @@
+---
+language: zh
+---
+
 # ernie-health-zh
 
 ## Introduction
 ERNIE-health is a Chinese biomedical language model pre-trained from in-domain text of de-identified online doctor-patient dialogues, electronic medical records, and textbooks.
 
 More detail: 
-https://github.com/PaddlePaddle/Research/tree/master/KG/eHealth
-https://github.com/PaddlePaddle/PaddleNLP/tree/develop/model_zoo/ernie-health
+https://github.com/PaddlePaddle/PaddleNLP/blob/develop/model_zoo/ernie-health/
 https://arxiv.org/pdf/2110.07244.pdf
 
 ## Released Model Info
@@ -17,7 +20,7 @@ https://arxiv.org/pdf/2110.07244.pdf
 This released pytorch model is converted from the officially released PaddlePaddle ERNIE model and 
 a series of experiments have been conducted to check the accuracy of the conversion.
 
-- Official PaddlePaddle ERNIE repo:https://github.com/PaddlePaddle/Research/tree/master/KG/eHealth
+- Official PaddlePaddle ERNIE repo:https://github.com/PaddlePaddle/PaddleNLP/blob/develop/model_zoo/ernie-health/
 - Pytorch Conversion repo:  https://github.com/nghuyong/ERNIE-Pytorch
 
 ## How to use

config.json

@@ -1,22 +1,20 @@
 {
     "attention_probs_dropout_prob": 0.1,
-    "directionality": "bidi",
     "embedding_size": 768,
     "hidden_act": "gelu",
     "hidden_dropout_prob": 0.1,
     "hidden_size": 768,
     "initializer_range": 0.02,
     "intermediate_size": 3072,
-    "layer_norm_eps": 1e-05,
     "max_position_embeddings": 512,
-    "model_type": "electra",
     "num_attention_heads": 12,
     "num_hidden_layers": 12,
     "pad_token_id": 0,
-    "summary_activation": "gelu",
-    "summary_last_dropout": 0.1,
-    "summary_type": "first",
-    "summary_use_proj": true,
     "type_vocab_size": 2,
-    "vocab_size": 22608
+    "vocab_size": 22608,
+    "layer_norm_eps": 1e-05,
+    "model_type": "bert",
+    "architectures": [
+        "BertModel"
+    ]
 }

pytorch_model.bin

@@ -1,3 +1,3 @@
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+oid sha256:4ce1d6a2b89ca225c48a6a407ef553d6a5d54cf5d45551587f41c0cdff2280de
 size 411317367