Update app.py

app.py

@@ -1,43 +1,44 @@
 import gradio as gr
 
-# def greet(name):
-#     return "Hello " + name + "!!"
+def greet(name):
+    return "Hello " + name + "!!"
 
 import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM,  BitsAndBytesConfig
 from peft import PeftModel, PeftConfig
 
-class InferenceFineTunning:
-    def __init__(self, model_path):
-        peft_model_id = f"hyang0503/{model_path}"
-        config = PeftConfig.from_pretrained(peft_model_id)
-        bnb_config = BitsAndBytesConfig(
-            load_in_4bit=True,
-            bnb_4bit_use_double_quant=True,
-            bnb_4bit_quant_type="nf4",
-            bnb_4bit_compute_dtype=torch.bfloat16
-        )
-        self.model = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path, quantization_config=bnb_config, device_map="auto")
-        self.model = PeftModel.from_pretrained(self.model, peft_model_id)
+# class InferenceFineTunning:
+#     def __init__(self, model_path):
+#         peft_model_id = f"hyang0503/{model_path}"
+#         config = PeftConfig.from_pretrained(peft_model_id)
+#         bnb_config = BitsAndBytesConfig(
+#             load_in_4bit=True,
+#             bnb_4bit_use_double_quant=True,
+#             bnb_4bit_quant_type="nf4",
+#             bnb_4bit_compute_dtype=torch.bfloat16
+#         )
+#         self.model = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path, quantization_config=bnb_config, device_map="auto")
+#         self.model = PeftModel.from_pretrained(self.model, peft_model_id)
         
-        # self.tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
-        self.tokenizer = AutoTokenizer.from_pretrained(peft_model_id)
-        self.tokenizer.pad_token = self.tokenizer.eos_token
-        self.model.eval()
+#         # self.tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
+#         self.tokenizer = AutoTokenizer.from_pretrained(peft_model_id)
+#         self.tokenizer.pad_token = self.tokenizer.eos_token
+#         self.model.eval()
 
-    def generate(self, q): # 실습 노트북과 내용 다름
-        outputs = self.model.generate(
-            **self.tokenizer(
-                f"### 질문: {q}\n\n### 답변:",
-                return_tensors='pt',
-                return_token_type_ids=False
-            ).to("cuda"),
-            max_new_tokens=256,
-            early_stopping=True,
-            do_sample=True,
-            eos_token_id=2,
-        )
-        print(self.tokenizer.decode(outputs[0]))
-ifg = InferenceFineTunning("qlora-koalpaca")
-iface = gr.Interface(fn=ifg.generate, inputs="text", outputs="text")
+#     def generate(self, q): # 실습 노트북과 내용 다름
+#         outputs = self.model.generate(
+#             **self.tokenizer(
+#                 f"### 질문: {q}\n\n### 답변:",
+#                 return_tensors='pt',
+#                 return_token_type_ids=False
+#             ).to("cuda"),
+#             max_new_tokens=256,
+#             early_stopping=True,
+#             do_sample=True,
+#             eos_token_id=2,
+#         )
+#         print(self.tokenizer.decode(outputs[0]))
+# ifg = InferenceFineTunning("qlora-koalpaca")
+# iface = gr.Interface(fn=ifg.generate, inputs="text", outputs="text")
+iface = gr.Interface(fn=greet, inputs="text", outputs="text")
 iface.launch()