Upload app.py

app.py

@@ -4,7 +4,7 @@ from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
 
 # Load model and tokenizer
-model_id = "Equall/SaulLM-141B-Instruct"
+model_id = "Equall/SaulLM-54B-Instruct"
 tokenizer = AutoTokenizer.from_pretrained(model_id)
 model = AutoModelForCausalLM.from_pretrained(
     model_id,
@@ -14,7 +14,7 @@ model = AutoModelForCausalLM.from_pretrained(
 
 @spaces.GPU()
 def generate_response(message, history, system_prompt, max_tokens, temperature):
-    """Generate legal analysis using Saul-141B"""
+    """Generate legal analysis using Saul-54B"""
     
     # Build conversation history
     messages = []
@@ -45,7 +45,7 @@ def generate_response(message, history, system_prompt, max_tokens, temperature):
     return response
 
 # Default system prompt for legal queries
-DEFAULT_SYSTEM = """You are SaulLM-141B, a specialized legal language model. You provide accurate legal analysis based on U.S. and European legal systems. 
+DEFAULT_SYSTEM = """You are SaulLM-54B, a specialized legal language model. You provide accurate legal analysis based on U.S. and European legal systems. 
 
 IMPORTANT DISCLAIMERS:
 - This is for informational purposes only, not legal advice
@@ -55,7 +55,7 @@ IMPORTANT DISCLAIMERS:
 
 # Build interface
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# SaulLM-141B Legal Assistant")
+    gr.Markdown("# SaulLM-54B Legal Assistant")
     gr.Markdown("*Specialized AI for legal reasoning and analysis. Private queries, powered by Zero GPU (25 min/day free).*")
     
     with gr.Row():