Update app.py

app.py

@@ -69,7 +69,7 @@ def run_training(hf_token, model_name, new_repo_name, lora_r, lora_alpha, lora_d
 
     def load_single(ds_name, cfg):
         try:
-            ds = load_dataset(ds_name, cfg, streaming=True, trust_remote_code=True)
+            ds = load_dataset(ds_name, cfg, streaming=True)
             if isinstance(ds, dict):
                 ds = next(iter(ds.values()))
             
@@ -117,7 +117,7 @@ def run_training(hf_token, model_name, new_repo_name, lora_r, lora_alpha, lora_d
 
     progress(0.3, desc="Cargando Tokenizer...")
     try:
-        tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True, padding_side="left", add_eos_token=True, add_bos_token=True)
+        tokenizer = AutoTokenizer.from_pretrained(model_name, padding_side="left", add_eos_token=True, add_bos_token=True)
         tokenizer.pad_token = tokenizer.eos_token
     except Exception as e:
         return f"Error cargando tokenizer: {str(e)}"
@@ -167,7 +167,7 @@ def run_training(hf_token, model_name, new_repo_name, lora_r, lora_alpha, lora_d
 
     progress(0.4, desc="Cargando Modelo...")
     try:
-        original_model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True)
+        original_model = AutoModelForCausalLM.from_pretrained(model_name)
     except Exception as e:
         return f"Error cargando modelo: {str(e)}"