Update app to load model from Hugging Face Hub instead of local files

config.json

@@ -0,0 +1,37 @@
+{
+  "_name_or_path": "ProsusAI/finbert",
+  "architectures": [
+    "BertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "classifier_dropout": null,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "positive",
+    "1": "negative",
+    "2": "neutral"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "negative": 1,
+    "neutral": 2,
+    "positive": 0
+  },
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "bert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "torch_dtype": "float32",
+  "transformers_version": "4.46.3",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 30522
+}

config.yaml

@@ -1 +1 @@
-model_path: "model_checkpoint"
+model_path: "utyug1/finbert-finetuned-model"

special_tokens_map.json

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

tokenizer_config.json

@@ -0,0 +1,57 @@
+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
+  "cls_token": "[CLS]",
+  "do_basic_tokenize": true,
+  "do_lower_case": true,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "never_split": null,
+  "pad_token": "[PAD]",
+  "sep_token": "[SEP]",
+  "strip_accents": null,
+  "tokenize_chinese_chars": true,
+  "tokenizer_class": "BertTokenizer",
+  "unk_token": "[UNK]"
+}

upload_model.py

@@ -0,0 +1,50 @@
+#!/usr/bin/env python3
+"""
+Script to upload the finetuned FinBERT model to Hugging Face Hub.
+"""
+
+import os
+from huggingface_hub import HfApi, create_repo, Repository
+
+def upload_model():
+    """Upload the finetuned model to Hugging Face Hub."""
+    
+    # Repository name (using the same name as the Space)
+    repo_name = "utyug1/finbert-finetuned-model"
+    
+    try:
+        # Create repository if it doesn't exist
+        print(f"Creating repository: {repo_name}")
+        create_repo(repo_name, exist_ok=True, private=False)
+        
+        # Clone the repository locally
+        print("Cloning repository...")
+        repo = Repository(repo_name, clone_from=repo_name)
+        
+        # Copy model files to the repository
+        print("Copying model files...")
+        model_dir = "model_chekpoint"
+        
+        for filename in os.listdir(model_dir):
+            file_path = os.path.join(model_dir, filename)
+            if os.path.isfile(file_path):
+                print(f"Copying {filename}...")
+                import shutil
+                shutil.copy2(file_path, filename)
+        
+        # Commit and push
+        print("Committing and pushing...")
+        repo.git_add()
+        repo.git_commit("Upload finetuned FinBERT model")
+        repo.git_push()
+        
+        print(f"Model successfully uploaded to: https://huggingface.co/{repo_name}")
+        
+    except Exception as e:
+        print(f"Error uploading model: {str(e)}")
+        return False
+    
+    return True
+
+if __name__ == "__main__":
+    upload_model()