Update app.py

app.py

@@ -4,23 +4,15 @@ import gradio as gr
 from peft import PeftModel, PeftConfig
 from peft import AutoPeftModelForCausalLM
 from transformers import AutoTokenizer
-# model = AutoPeftModelForCausalLM.from_pretrained(
-#         "FlawedLLM/BhashiniLLM", # YOUR MODEL YOU USED FOR TRAINING
-#         load_in_4bit = True,
-# )
-# tokenizer = AutoTokenizer.from_pretrained("FlawedLLM/BhashiniLLM")
-from unsloth import FastLanguageModel
+model = AutoPeftModelForCausalLM.from_pretrained(
+        "FlawedLLM/BhashiniLLM", # YOUR MODEL YOU USED FOR TRAINING
+        load_in_4bit = True,
+)
+tokenizer = AutoTokenizer.from_pretrained("FlawedLLM/BhashiniLLM")
 
 
 @spaces.GPU(duration=300)
 def chunk_it(input_command):
-    model, tokenizer = FastLanguageModel.from_pretrained(
-            model_name = "FlawedLLM/BhashiniLLM", # YOUR MODEL YOU USED FOR TRAINING
-            max_seq_length = 2048,
-            dtype = None,
-            load_in_4bit = True,
-    )
-    FastLanguageModel.for_inference(model)
     alpaca_prompt = """Below is an instruction that describes a task, paired with an input that provides further context. Write a response that appropriately completes the request.
     
     ### Instruction: