Upload config

config.json

@@ -1,10 +1,6 @@
 {
-  "architectures": [
-    "SententenceTransformerSentimentModel"
-  ],
   "auto_map": {
-    "AutoConfig": "config.SentimentConfig",
-    "AutoModelForSequenceClassification": "model.SententenceTransformerSentimentModel"
+    "AutoConfig": "model.SentimentConfig"
   },
   "class_map": {
     "0": "sad",
@@ -18,6 +14,5 @@
   "h1": 44,
   "h2": 46,
   "model_type": "SententenceTransformerSentimentClassifier",
-  "torch_dtype": "float32",
   "transformers_version": "4.29.0"
 }

model.py

@@ -1,9 +1,22 @@
-from config import SentimentConfig
 from transformers import PreTrainedModel
 import torch.nn as nn
 import torch.nn.functional as F
+from transformers import PretrainedConfig
 
 
+mp = {0:'sad',1:'joy',2:'love',3:'anger',4:'fear',5:'surprise'}
+
+class SentimentConfig(PretrainedConfig):
+    model_type = "SententenceTransformerSentimentClassifier"
+
+    def __init__(self, embedding_model: str="sentence-transformers/all-MiniLM-L6-v2", class_map: dict=mp, h1: int=44, h2: int=46, **kwargs):
+        self.embedding_model = embedding_model
+        self.class_map = class_map
+        self.h1 = h1
+        self.h2 = h2
+
+        super().__init__(**kwargs)
+
 class SententenceTransformerSentimentModel(PreTrainedModel):
     config_class = SentimentConfig