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c61c393 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | """Text generation wrapper."""
import torch
from typing import List, Dict
from .model_loader import load_model
def generate_text(messages: List[Dict[str, str]], model_name: str, max_new_tokens: int = 80):
model, tokenizer = load_model(model_name)
inputs = tokenizer.apply_chat_template(
messages, tokenize=True, return_tensors="pt",
add_generation_prompt=True, return_dict=True,
)
dev = next(model.parameters()).device
inputs = {k: v.to(dev) for k, v in inputs.items()}
with torch.no_grad():
outputs = model.generate(
**inputs, max_new_tokens=max_new_tokens,
do_sample=False, pad_token_id=tokenizer.pad_token_id,
)
gen = outputs[0][inputs["input_ids"].shape[1]:]
return tokenizer.decode(gen, skip_special_tokens=True).strip()
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