Update app.py

app.py

@@ -1,10 +1,19 @@
 import pandas as pd
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformers import AutoTokenizer, AutoModelForCausalLM, AutoConfig
 
-# Load the model and tokenizer for Meta LLaMA 3.1
+# Load the configuration and adjust it
+config = AutoConfig.from_pretrained("meta-llama/Meta-Llama-3.1-8B")
+if 'rope_scaling' in config.to_dict() and isinstance(config.rope_scaling, dict):
+    # Adjust the rope_scaling to match the expected format
+    config.rope_scaling = {
+        "type": config.rope_scaling.get('rope_type', 'llama3'),
+        "factor": config.rope_scaling.get('factor', 8.0)
+    }
+
+# Load the tokenizer and model with the adjusted configuration
 tokenizer = AutoTokenizer.from_pretrained("meta-llama/Meta-Llama-3.1-8B")
-model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3.1-8B")
+model = AutoModelForCausalLM.from_config(config)
 
 # Load and preprocess the DataFrame
 df = pd.read_csv('anomalies.csv')