hh

app.py

@@ -1,44 +1,48 @@
 import gradio as gr
+import re
 from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
 
 # Загрузка модели и токенизатора
-model_name = "microsoft/DialoGPT-medium"
+model_name = "Dennterry/okt_bot"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForCausalLM.from_pretrained(model_name)
 
-# Создаем pipeline для генерации диалогов
-generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
-
 def respond(message, history, system_message, max_tokens, temperature, top_p):
     # Формируем текст, который будет передан в модель
-    input_text = system_message + " ".join([f"User: {msg[0]} Assistant: {msg[1]}" for msg in history if msg[0] and msg[1]])
-    input_text += f"User: {message}"
+    inputs = tokenizer(f'@@ПЕРВЫЙ@@{message}@@ВТОРОЙ@@', return_tensors='pt')
 
-    # Генерация ответа
-    response = generator(
-        input_text,
-        max_length=len(tokenizer.encode(input_text)) + max_tokens,
-        temperature=temperature,
+    generated_token_ids = model.generate(
+        **inputs,
+        top_k=50,
         top_p=top_p,
-        pad_token_id=tokenizer.eos_token_id,
-        num_return_sequences=1,
+        num_beams=5,
+        num_return_sequences=3,
+        do_sample=True,
+        no_repeat_ngram_size=2,
+        temperature=temperature,
+        repetition_penalty=1.5,
+        length_penalty=0.6,
+        eos_token_id=50257,
+        max_new_tokens=max_tokens
     )
 
     # Извлечение и возврат текста ответа
-    output_text = response[0]['generated_text'][len(input_text):]
-    yield output_text.strip()
+    context_with_response = [tokenizer.decode(sample_token_ids) for sample_token_ids in generated_token_ids]
+    result1 = re.sub(r'@@.*?@@', '', context_with_response[0])
+    result2 = result1[len(a):]
+    yield result2.strip()
 
 # Настройка интерфейса Gradio
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox(value="Тебя зовут зевибот. Ты ваще никому ничо не должен.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=1.0, step=0.1, label="Temperature"),
+        gr.Textbox(value="Чебупели", label="System message"),
+        gr.Slider(minimum=1, maximum=2048, value=100, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=1.2, step=0.1, label="Temperature"),
         gr.Slider(
             minimum=0.1,
             maximum=1.0,
-            value=1.0, step=0.05, label="Top-p (nucleus sampling)"
+            value=0.95, step=0.05, label="Top-p (nucleus sampling)"
         ),
     ],
 )