Update app.py

app.py

@@ -1,12 +1,18 @@
 import gradio as gr
 import transformers as t
 import torch
+import peft
 
 # Load your fine-tuned model and tokenizer
-model = t.AutoModelForCausalLM.from_pretrained("./weights")
 tokenizer = t.AutoTokenizer.from_pretrained("NousResearch/Llama-2-7b-hf")
+model = t.AutoModelForCausalLM.from_pretrained("NousResearch/Llama-2-7b-hf", load_in_8bit=True, torch_dtype=torch.float16)
 tokenizer.pad_token_id = 0
 
+config = peft.LoraConfig(r=8, lora_alpha=16, target_modules=["q_proj", "v_proj"], lora_dropout=0.005, bias="none", task_type="CAUSAL_LM")
+model = peft.get_peft_model(model, config)
+
+peft.set_peft_model_state_dict(model, torch.load(f"./output/checkpoint-{checkpoint}/adapter_model.bin"))
+
 # Define a prediction function
 def generate_article(title):
     prompt = f"Below is a title for an article. Write an article that appropriately suits the title: \n\n### Title:\n{title}\n\n### Article:\n"