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app.py

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+import streamlit as st
+import pandas as pd
+import numpy as np
+
+import torch
+from transformers import pipeline
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+
+st.title('Marcel Proust')
+st.subheader("Commencez la phrase, l'algorithme la termine.")
+st.write("Note : la génération du texte prend ~ 5 minutes")
+
+
+
+
+with st.form("my_form"):
+   
+   text = st.text_input("Début de la phrase :", 'Je me souvenais de ce jour où Jean-Michel')
+   
+   # Every form must have a submit button.
+   submitted = st.form_submit_button("Générer la suite")
+   
+   # Load the model ---
+   model_checkpoint = "bigscience/bloom-560m"
+   tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)
+   model = AutoModelForCausalLM.from_pretrained("dan-vdb/ProustAI")
+   device = torch.device("cpu")
+
+   # device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
+
+   pipe = pipeline(
+    "text-generation", model=model, tokenizer=tokenizer, device=device
+   )
+   # ---
+
+   
+   if submitted:
+       st.write(pipe(text, num_return_sequences=1, max_length=100)[0]["generated_text"])

requirements.txt

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+numpy==1.24.0
+pandas==1.5.2
+streamlit==1.16.0
+torch==1.12.1
+transformers==4.24.0