Update pages/gpt.py

pages/gpt.py

@@ -5,7 +5,7 @@ import textwrap
 import plotly.express as px
 
 
-st.header(':green[Генерация текста GPT-моделью]')
+st.header(':green[Text generation by GPT2 model]')
 
 tokenizer = GPT2Tokenizer.from_pretrained('sberbank-ai/rugpt3small_based_on_gpt2')
 model = GPT2LMHeadModel.from_pretrained(
@@ -13,25 +13,25 @@ model = GPT2LMHeadModel.from_pretrained(
     output_attentions = False,
     output_hidden_states = False,
 )
-# Вешаем сохраненные веса на нашу модель
+
 model.load_state_dict(torch.load('models/modelgpt.pt', map_location=torch.device('cpu')))
 
 
-length = st.sidebar.slider('**Длина генерируемой последовательности:**', 8, 256, 15)
+length = st.sidebar.slider('**Generated sequence length:**', 8, 256, 15)
 if length > 100:
-    st.warning("this is very hard for me, please have pity on me", icon="🤖")
-num_samples = st.sidebar.slider('**Число генераций:**', 1, 10, 1)
+    st.warning("This is very hard for me, please have pity on me. Could you lower the value?", icon="🤖")
+num_samples = st.sidebar.slider('**Number of generations:**', 1, 10, 1)
 if num_samples > 4:
-    st.warning("OH MY ..., I have to work late again!!!", icon="🤖")
-temperature = st.sidebar.slider('**Температура:**', 0.1, 10.0, 3.0)
-if num_samples > 6.0:
-    st.info('What? You want to get some kind of bullshit as a result?', icon="🤖")
-top_k = st.sidebar.slider('**Количество наиболее вероятных слов генерации:**', 10, 200, 50)
-top_p = st.sidebar.slider('**Минимальная суммарная вероятность топовых слов:**', 0.4, 1.0, 0.9)
+    st.warning("OH MY ..., I have to work late again!!! Could you lower the value", icon="🤖")
+temperature = st.sidebar.slider('**Temperature:**', 0.1, 10.0, 3.0)
+if temperature > 6.0:
+    st.info('What? You want to get some kind of bullshit as a result? Turn down the temperature', icon="🤖")
+top_k = st.sidebar.slider('**Number of most likely generation words:**', 10, 200, 50)
+top_p = st.sidebar.slider('**Minimum total probability of top words:**', 0.4, 1.0, 0.9)
 
 
-prompt = st.text_input('**Введите текст 👇:**')
-if st.button('**Сгенерировать текст**'):
+prompt = st.text_input('**Enter text 👇:**')
+if st.button('**Generate text**'):
  
     with torch.inference_mode():
         prompt = tokenizer.encode(prompt, return_tensors='pt')