add model and inference function

app.py

@@ -1,7 +1,31 @@
 import gradio as gr
+import torch
+from transformers import AutoTokenizer
+from transformers import AutoModelForSequenceClassification
 
-def greet(name):
-    return "Hello " + name + "!!"
+    
+# Specify the path of the model
+model_ckpt = Path("./distilbert-base-uncased-finetuned-emotion")
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+# Load the fine-tuned tokenizer and model
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+tokenizer = AutoTokenizer.from_pretrained(model_ckpt)
+model = AutoModelForSequenceClassification.from_pretrained(model_ckpt).to(device)
+
+class_names = ['sadness', 'joy', 'love', 'anger', 'fear', 'surprise']
+
+
+def inference(text: str) -> str:
+    inputs = tokenizer(text, return_tensors="pt")
+
+    inputs = {k:v.to(device) for k,v in inputs.items()}
+    with torch.no_grad():
+        outputs = model(**inputs)
+    predictions = torch.nn.functional.softmax(outputs.logits, dim=-1).tolist()[0]
+
+    max_vale = max(predictions)
+    idx = predictions.index(max_vale)
+    return model.config.id2label[idx]
+
+iface = gr.Interface(fn=inference, inputs="text", outputs="text")
 iface.launch()

distilbert-base-uncased-finetuned-emotion/config.json

@@ -0,0 +1,41 @@
+{
+  "_name_or_path": "distilbert-base-uncased",
+  "activation": "gelu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
+  "attention_dropout": 0.1,
+  "dim": 768,
+  "dropout": 0.1,
+  "hidden_dim": 3072,
+  "id2label": {
+    "0": "sadness",
+    "1": "joy",
+    "2": "love",
+    "3": "anger",
+    "4": "fear",
+    "5": "surprise"
+  },
+  "initializer_range": 0.02,
+  "label2id": {
+    "anger": 3,
+    "fear": 4,
+    "joy": 1,
+    "love": 2,
+    "sadness": 0,
+    "surprise": 5
+  },
+  "max_position_embeddings": 512,
+  "model_type": "distilbert",
+  "n_heads": 12,
+  "n_layers": 6,
+  "pad_token_id": 0,
+  "problem_type": "single_label_classification",
+  "qa_dropout": 0.1,
+  "seq_classif_dropout": 0.2,
+  "sinusoidal_pos_embds": false,
+  "tie_weights_": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.28.1",
+  "vocab_size": 30522
+}

distilbert-base-uncased-finetuned-emotion/pytorch_model.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:781800fb16c200d330072a7d2b95bd7b3d34054b3f3f33023bf3020b96406a2a
+size 267866413

distilbert-base-uncased-finetuned-emotion/special_tokens_map.json

@@ -0,0 +1,7 @@
+{
+  "cls_token": "[CLS]",
+  "mask_token": "[MASK]",
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "unk_token": "[UNK]"
+}

distilbert-base-uncased-finetuned-emotion/test_metrics.csv

@@ -0,0 +1,2 @@
+test_loss,test_accuracy,test_f1,test_runtime,test_samples_per_second,test_steps_per_second
+0.21811038255691528,0.92,0.919083343174122,25.5537,78.266,1.252

distilbert-base-uncased-finetuned-emotion/tokenizer_config.json

@@ -0,0 +1,13 @@
+{
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "DistilBertTokenizer",
+  "unk_token": "[UNK]"
+}

distilbert-base-uncased-finetuned-emotion/training_args.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ebcad4e947ae20ae35cf3bdf68a31a91b16facc628995d5448c2ed9bb76a3351
+size 3643