diana-salgado commited on
Commit
c0062d3
·
1 Parent(s): 7fd1156

Correction in app file

Browse files

Change the model_path from local to the one in the hub

Files changed (1) hide show
  1. app.py +12 -5
app.py CHANGED
@@ -2,12 +2,12 @@ from transformers import AutoModelForSequenceClassification, AutoTokenizer
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  import torch
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  import gradio as gr
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- # Cargar modelo entrenado
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- model_path = r"C:\Users\diana\OneDrive\Documentos\Escuela\Semestre 8\T.S_PLN\st-cl-2025-2-lab\practicas\dianasalgado22\P6\Ejecuciones\runs\Model_delarosajav95_HateSpeech-BETO-cased-v2\250508T132050\bestModel"
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- model = AutoModelForSequenceClassification.from_pretrained(model_path)
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- tokenizer = AutoTokenizer.from_pretrained(model_path)
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  # Diccionario de etiquetas
 
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  label_map = {0: "No sexista", 1: "Sexista"}
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  def predict(text):
@@ -17,6 +17,13 @@ def predict(text):
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  probs = torch.nn.functional.softmax(logits, dim=1)
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  return {label_map[i]: float(p) for i, p in enumerate(probs[0])}
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-
 
 
 
 
 
 
 
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  iface.launch()
 
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  import torch
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  import gradio as gr
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+ # Carga del modelo desde Hugging Face Hub
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+ model = AutoModelForSequenceClassification.from_pretrained("diana-salgado/Detector-Sexismo-Espanol")
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+ tokenizer = AutoTokenizer.from_pretrained("diana-salgado/Detector-Sexismo-Espanol")
 
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  # Diccionario de etiquetas
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+
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  label_map = {0: "No sexista", 1: "Sexista"}
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  def predict(text):
 
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  probs = torch.nn.functional.softmax(logits, dim=1)
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  return {label_map[i]: float(p) for i, p in enumerate(probs[0])}
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+ iface = gr.Interface(
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+ fn=predict,
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+ inputs=gr.Textbox(lines=3, placeholder="Escribe tu texto aquí..."),
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+ outputs=gr.Label(num_top_classes=2),
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+ title="Clasificador de Tweets: Sexista vs No Sexista",
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+ description="Este modelo clasifica oraciones en español como sexistas o no sexistas.",
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+ article="Este modelo fue fine-tuned usando `delarosajav95/HateSpeech-BETO-cased-v2` sobre el corpus de EXIST 2024."
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+ )
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  iface.launch()