Upload final - 복사본.py

final - 복사본.py

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+from transformers import AutoTokenizer, AutoModelForCausalLM, AdamW
+import transformers
+import torch
+import numpy as np
+from torch.optim import lr_scheduler
+import torch.optim as optim
+from accelerate import Accelerator
+import os
+import json
+import jsonlines
+import pandas as pd
+import gradio as gr
+
+
+from torch.utils.data import Dataset as Dataset2
+
+from datasets import load_dataset, Dataset, Features, Value
+
+from peft import prepare_model_for_kbit_training, LoraConfig, get_peft_model, PeftModel, PeftConfig
+
+title = "🤖응답하라 챗봇🤖"
+description = "특정 도메인에 특화된 챗봇"
+examples = [["특허란 무엇인가요?"], ["자동차에 관한 특허는 무엇이 있나요?"], ]
+
+def gen(input, history):
+    gened = model.generate(
+        **tokenizer(
+            f"##질문:{input}\n##답변:",
+            return_tensors='pt',
+            return_token_type_ids=False
+        ).to('cuda'),
+        max_new_tokens=256,
+        no_repeat_ngram_size=6,
+        # top_p=0.8,
+        temperature=0.7,
+        early_stopping=True,
+        # num_return_sequences=5,
+        do_sample=True,
+        eos_token_id=2,
+        pad_token_id=2
+    )
+    # print(gened[0])
+    return tokenizer.decode(gened[0])
+    
+    
+model_root = "polyglot-ko-1.3b-lora-knk"
+model_name = 'polyglot-ko-1.3b-base-knk'
+
+# config = LoraConfig(
+#     r=8,
+#     lora_alpha=32, # 32
+#     target_modules=["query_key_value"],
+#     lora_dropout=0.05,
+#     bias="none",
+#     task_type="CAUSAL_LM"
+# )
+
+config = PeftConfig.from_pretrained(model_root)
+tokenizer = AutoTokenizer.from_pretrained('EleutherAI/polyglot-ko-1.3b')
+model = AutoModelForCausalLM.from_pretrained(config.base_model_name_or_path, device_map={"":0})
+# model.eval()
+model = PeftModel.from_pretrained(model, model_root)
+
+# model = prepare_model_for_kbit_training(model)
+# model = get_peft_model(model, config)
+
+model.eval()
+model.config.use_cache = True  # silence the warnings. Please re-enable for inference!
+
+"""
+while 1:
+    ques = input('질문:')
+    if ques == '1': break
+    gen(ques)
+"""
+demo = gr.ChatInterface(
+    fn=gen, 
+    title=title,
+    description=description,
+    examples=examples,
+    theme="xiaobaiyuan/theme_brief",
+    )
+    
+if __name__ == "__main__":
+    demo.launch(share=True)