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# generate.py
import torch
from load_model import get_model
def generate_response(
user_prompt: str,
system_prompt: str = "You are a helpful AI assistant.",
max_tokens: int = 256,
temperature: float = 0.2,
) -> str:
"""Generate response using ALREADY LOADED model"""
model, tokenizer = get_model() # Fast - no loading!
messages = [
{"role": "system", "content": system_prompt},
{"role": "user", "content": user_prompt},
]
input_ids = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
return_tensors="pt",
).to(model.device)
attention_mask = (input_ids != tokenizer.pad_token_id).long()
do_sample = temperature > 0.0
gen_kwargs = dict(
input_ids=input_ids,
attention_mask=attention_mask,
max_new_tokens=max_tokens,
pad_token_id=tokenizer.eos_token_id,
use_cache=False,
do_sample=do_sample,
)
if do_sample:
gen_kwargs["temperature"] = float(temperature)
gen_kwargs["top_p"] = 0.95
with torch.no_grad():
outputs = model.generate(**gen_kwargs)
return tokenizer.decode(
outputs[0][input_ids.shape[1]:],
skip_special_tokens=True,
).strip()
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