File size: 899 Bytes
50a8ea3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import torch
def generate_rti_draft(complaint_text: str, model_id: str = "CaseLoop/rti-formatter") -> str:
"""Loads the fine-tuned T5 formatter from Hugging Face and generates a structured RTI draft."""
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForSeq2SeqLM.from_pretrained(model_id)
prompt = f"Format as RTI: {complaint_text}"
inputs = tokenizer(prompt, return_tensors="pt")
with torch.no_grad():
outputs = model.generate(
**inputs,
max_new_tokens=256,
num_beams=4,
no_repeat_ngram_size=3, # Prevents repeated loops
repetition_penalty=2.0, # Penalizes word/phrase repetition
early_stopping=True
)
return tokenizer.decode(outputs[0], skip_special_tokens=True) |