Delete streamlit.py

streamlit.py

@@ -1,45 +0,0 @@
-import streamlit as st
-from transformers import GPT2LMHeadModel, GPT2Tokenizer
-
-@st.cache(allow_output_mutation=True)
-def load_model():
-    '''
-    Loads the model and tokenizer from the local directory.
-    :return: A list containing the model and the tokenizer.
-    '''
-    model_name = 'WIP'
-    tokenizer = GPT2Tokenizer.from_pretrained(model_name)
-    model = GPT2LMHeadModel.from_pretrained(model_name)
-    return [model, tokenizer]
-
-st.set_page_config(
-    page_title="BulgakovLM Example",
-    page_icon="👨‍💻",
-)
-
-st.markdown("# 👨‍💻 BulgakovLM Example")
-
-txt = st.text_area('Write code here', '''Однажды утром''', height=400)
-
-gen = st.button('Generate')
-
-c = st.code('')
-
-max_length = st.slider('max_length', 1, 1024, 128)
-top_k = st.slider('top_k', 0, 100, 50)
-top_p = st.slider('top_p', 0.0, 1.0, 0.9)
-temperature = st.slider('temperature', 0.0, 1.0, 1.0)
-num_beams = st.slider('num_beams', 1, 100, 5)
-repetition_penalty = st.slider('repetition_penalty', 1.0, 10.0, 1.0)
-
-
-if gen:
-    c.code('Generating...')
-    m = load_model()
-
-    inpt = m[1].encode(txt, return_tensors="pt")
-    out = m[0].generate(inpt, max_length=max_length, top_p=top_p, top_k=top_k, temperature=temperature, num_beams=num_beams, repetition_penalty=repetition_penalty)
-    res = m[1].decode(out[0])
-
-    print('ok')
-    c.code(res)