TEST_10

app.py

@@ -2,29 +2,27 @@ import gradio as gr
 from transformers import pipeline
 from sentence_transformers import SentenceTransformer, util
 
-# Carregamento dos modelos
-model_a = pipeline("text-generation", model="tiiuae/falcon-7b-instruct")
-model_b = pipeline("text-generation", model="mistralai/Mistral-7B-Instruct-v0.1")
+generator_a = pipeline("text-generation", model="gpt2")
+generator_b = pipeline("text2text-generation", model="google/flan-t5-base")
 similarity_model = SentenceTransformer("sentence-transformers/paraphrase-MiniLM-L6-v2")
 
-def comparar_respostas(prompt):
-    resp_a = model_a(prompt, max_new_tokens=80)[0]["generated_text"]
-    resp_b = model_b(prompt, max_new_tokens=80)[0]["generated_text"]
+def comparar(prompt):
+    resp_a = generator_a(prompt, max_new_tokens=60, temperature=0.7)[0]["generated_text"]
+    resp_b = generator_b(prompt, max_new_tokens=60, temperature=0.7)[0]["generated_text"]
+
     emb_a = similarity_model.encode(resp_a, convert_to_tensor=True)
     emb_b = similarity_model.encode(resp_b, convert_to_tensor=True)
     similaridade = util.cos_sim(emb_a, emb_b).item()
 
     return resp_a.strip(), resp_b.strip(), f"{similaridade:.4f}"
 
-interface = gr.Interface(
-    fn=comparar_respostas,
-    inputs=gr.Textbox(label="Digite seu prompt"),
+gr.Interface(
+    fn=comparar,
+    inputs=gr.Textbox(label="Digite um prompt"),
     outputs=[
-        gr.Textbox(label="Resposta do Modelo A (Falcon)"),
-        gr.Textbox(label="Resposta do Modelo B (Mistral)"),
-        gr.Textbox(label="Similaridade entre as respostas")
+        gr.Textbox(label="Resposta do GPT-2"),
+        gr.Textbox(label="Resposta do Flan-T5"),
+        gr.Textbox(label="Similaridade entre respostas")
     ],
-    title="Comparador de Modelos LLM - Hugging Face"
-)
-
-interface.launch()
+    title="Comparador de Modelos LLM Leves"
+).launch()