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57eb232 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
import torch
MODEL_PATH = "."
tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH)
model = AutoModelForSeq2SeqLM.from_pretrained(MODEL_PATH)
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
model.to(device)
def ask_resume_bot(question):
prompt = f"Answer this resume question: {question}"
inputs = tokenizer(prompt, return_tensors="pt", truncation=True).to(device)
with torch.no_grad():
output = model.generate(
**inputs,
max_new_tokens=100,
num_beams=4
)
return tokenizer.decode(output[0], skip_special_tokens=True)
if __name__ == "__main__":
questions = [
"What is your educational background?",
"What are your technical skills?",
"Tell me about your medical X-ray project."
]
for q in questions:
print("Q:", q)
print("A:", ask_resume_bot(q))
print()
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