Update app.py

app.py

@@ -5,8 +5,8 @@ import torch
 import re
 
 # Initialize the model
-model = AutoModelForCausalLM.from_pretrained("Detsutut/Igea-1B-v0.0.1-Q4_K_M-GGUF")
-tokenizer = AutoTokenizer.from_pretrained( "Detsutut/Igea-350M-v0.0.1")
+model = AutoModelForCausalLM.from_pretrained("Detsutut/Igea-1B-v0.0.1-Q4_K_M-GGUF", model_file="igea-1b-v0.0.1-q4_k_m.gguf", model_type="mistral", hf=True)
+tokenizer = AutoTokenizer.from_pretrained( "Detsutut/Igea-1B-v0.0.1")
 
 
 gen_pipeline = pipeline(
@@ -16,7 +16,7 @@ gen_pipeline = pipeline(
 )
 
 # Define the function to generate text
-def generate_text(input_text, max_new_tokens, temperature, top_p, split_output):
+def generate_text(input_text, max_new_tokens=30, temperature=1, top_p=0.95, split_output=False):
     if split_output:
         max_new_tokens=30
         top_p=0.95