---
license: apache-2.0
---

## INFERENCE CODE
```bash
pip install transformers[torch]
```

```python
from transformers import AutoTokenizer, AutoModelForCausalLM, TextStreamer
import torch
import time

tokenizer = AutoTokenizer.from_pretrained("AquilaX-AI/DB-Summarizer")
model = AutoModelForCausalLM.from_pretrained("AquilaX-AI/DB-Summarizer")

device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")

question = "How many Vulnerability found today"
db_result = "243"
summ_inp = f"""<|im_start|>system
Generate a clear and accurate response based on the user's question and the database output.<|im_end|>
<|im_start|>user
user_question:
{question}
db_response:
{db_result}<|im_end|>
<|im_start|>assistant"""

import time
start = time.time()

encodeds = tokenizer(summ_inp, return_tensors="pt",truncation=True).input_ids.to(device)
model.to(device)

text_streamer = TextStreamer(tokenizer, skip_prompt = True)
response = model.generate(
        input_ids=encodeds,
        streamer=text_streamer,
        max_new_tokens=512,
        use_cache=True,
        pad_token_id=151645,
        eos_token_id=151645,
        num_return_sequences=1
    )

end = time.time()
print(f"Time taken: {end - start}")
```