woman

app.py

@@ -2,7 +2,6 @@ import gradio as gr
 from transformers import AutoTokenizer, AutoModelForCausalLM, AutoModelForSeq2SeqLM
 from PyPDF2 import PdfReader
 
-
 # Models and Tokenizers Setup
 models = {
     "Text Generator (Bloom)": {
@@ -11,11 +10,11 @@ models = {
     },
     "PDF Summarizer (T5)": {
         "model": AutoModelForSeq2SeqLM.from_pretrained("aaliyaan/t5-small-finetuned-career"),
-        "tokenizer": AutoTokenizer.from_pretrained("aaliyaan/t5-small-finetuned-career", use_fast=False),
+        "tokenizer": AutoTokenizer.from_pretrained("aaliyaan/t5-small-finetuned-career"),
     },
     "Broken Answer (T0pp)": {
         "model": AutoModelForSeq2SeqLM.from_pretrained("bigscience/T0pp"),
-        "tokenizer": AutoTokenizer.from_pretrained("bigscience/T0pp", use_fast=False),
+        "tokenizer": AutoTokenizer.from_pretrained("bigscience/T0pp"),
     },
 }
 
@@ -54,7 +53,6 @@ def chat_with_model(model_choice, user_message, chat_history, file=None):
 
 # Function to Extract Text from PDF
 def extract_text_from_pdf(file):
-    from PyPDF2 import PdfReader
     reader = PdfReader(file.name)
     text = "\n".join(page.extract_text() for page in reader.pages if page.extract_text())
     return text