Update app.py

app.py

@@ -1,7 +1,7 @@
 import gradio as gr
 import os, torch
 from datasets import load_dataset
-from huggingface_hub import HfApi
+from huggingface_hub import HfApi, login
 from transformers import AutoModelForCausalLM, AutoTokenizer, Seq2SeqTrainer, Seq2SeqTrainingArguments, pipeline
 
 ACTION_1 = "Prompt base model"
@@ -114,15 +114,18 @@ def fine_tune_model(base_model_name, dataset_name):
     
     #trainer.train()
 
-    # Save model to HF
+    # Save model and tokenizer to HF
 
-    api = HfApi()
+    login(token=os.environ["HF_TOKEN"])
     
+    api = HfApi()
+    api.create_repo(repo_id=FT_MODEL_NAME)
     api.upload_folder(
         folder_path="./output",
-        repo_id=FT_MODEL_NAME,
-        repo_type="model",
+        repo_id="Meta-Llama-3.1-8B-Instruct-text-to-sql"
     )
+
+    tokenizer.push_to_hub(FT_MODEL_NAME)
     
 def prompt_model(model_name, system_prompt, user_prompt, sql_context):
     pipe = pipeline("text-generation",