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SlotExtractor_MDM_Autonomo

Modelo BERT en español fine-tuned para clasificación de intenciones.

🧠 Arquitectura

  • Base: dccuchile/bert-base-spanish-wwm-cased
  • Idioma: Español

📊 Métricas

  • Accuracy: 0.967
  • Macro F1: 0.967

🔤 Intenciones (27)

  • 0 → add_reminder
  • 1 → analyze_image
  • 2 → archive_trello_cards
  • 3 → budget_control
  • 4 → contact_with_live_agent
  • 5 → create_image
  • 6 → create_lead
  • 7 → create_music
  • 8 → delete_reminder
  • 9 → get_drive_file
  • 10 → get_information
  • 11 → get_map
  • 12 → get_reminder
  • 13 → get_security_code
  • 14 → get_trello_cards
  • 15 → list_filenames
  • 16 → make_call
  • 17 → routine_tracking
  • 18 → search_filtered_exercises
  • 19 → search_information
  • 20 → search_products
  • 21 → send_email_attachment
  • 22 → send_gmail
  • 23 → simulate_operations
  • 24 → start_conversation
  • 25 → upload_drive_file
  • 26 → upload_image

⚙️ Uso rápido

from transformers import AutoTokenizer, AutoModelForSequenceClassification
MODEL_ID = 'ArmandoRockYourCloud/SlotExtractor_MDM_Autonomo'

tok = AutoTokenizer.from_pretrained(MODEL_ID)
model = AutoModelForSequenceClassification.from_pretrained(MODEL_ID)
id2label = model.config.id2label

text = 'Agrega un recordatorio para mañana a las 9'
enc = tok(text, return_tensors='pt', truncation=True, max_length=128)
with torch.no_grad():
    logits = model(**enc).logits
pred = logits.argmax(-1).item()
print(id2label[str(pred)])

🧾 Notas

  • config.json incluye los mapeos id2label y label2id.
  • labels.json se incluye como referencia adicional.
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