modifiquei a estrutura da API

app.py

@@ -1,16 +1,16 @@
 import streamlit as st
-from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+from transformers import T5Tokenizer, T5ForConditionalGeneration, pipeline
 
 # Substitua 'seu-nome-de-usuário/nome-do-modelo' pelo caminho correto do seu modelo no Hugging Face Hub
 MODEL_NAME = "exo-is/t5-small-60M-esg-keyword"
 
 @st.cache_resource
 def load_model():
-    tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME, use_fast=False)
-    model = AutoModelForCausalLM.from_pretrained(MODEL_NAME)
-    return pipeline('text-generation', model=model, tokenizer=tokenizer)
+    tokenizer = T5Tokenizer.from_pretrained(MODEL_NAME)
+    model = T5ForConditionalGeneration.from_pretrained(MODEL_NAME)
+    return pipeline('text2text-generation', model=model, tokenizer=tokenizer)
 
-st.title('Gerador de Texto')
+st.title('Gerador de Texto T5')
 
 gerador = load_model()
 

requirements.txt

@@ -1,4 +1,5 @@
 streamlit==1.25.0
 transformers==4.33.2
 torch==2.0.1
-tokenizers==0.13.3
+tokenizers==0.13.3
+sentencepiece==0.1.99