fix HF integration

this will fix the configuration problem you can test this pr before merging using the following code
```python
from transformers import AutoModelForSequenceClassification
# the revision parameter is only temporary and it should be removed after this pr is merged
# this will also fix the code snippet for the model
model2 = AutoModelForSequenceClassification.from_pretrained("KhaldiAbderrhmane/emotion-classifier-hubert",trust_remote_code = True,revision="refs/pr/1")
```

config.json

@@ -1,6 +1,14 @@
 {
+  "architectures": [
+    "EmotionClassifierHuBERT"
+  ],
+  "auto_map": {
+    "AutoConfig": "configuration_emotion_classifier.EmotionClassifierConfig",
+    "AutoModelForSequenceClassification": "modeling_emotion_classifier.EmotionClassifierHuBERT"
+  },
   "hidden_size_lstm": 128,
+  "model_type": "hubert",
   "num_classes": 6,
-  "transformers_version": "4.37.2"
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.1"
 }
-

configuration_emotion_classifier.py

@@ -1,8 +1,7 @@
 from transformers import PretrainedConfig
 
 class EmotionClassifierConfig(PretrainedConfig):
-
-
+    model_type = "hubert"
     def __init__(
         self,
         hidden_size_lstm =128,

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:959d79d116e1a22ccd3fd16b4e7f4c99b0e359cc67bce15458907db901e86a3c
-size 1278105600
+oid sha256:0c31d92b1b9d4de0f4bef72baff3625000148b627f99e3588ba540b35b203150
+size 1278105656