File size: 725 Bytes
f50b1b3 |
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 |
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
model_path = "./Path-to-llm-folder"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(model_path)
device = "cuda" if torch.cuda.is_available() else "cpu"
model.to(device)
def generate_text(prompt, max_length=2000):
inputs = tokenizer(prompt, return_tensors="pt").to(device)
output = model.generate(
**inputs,
do_sample=True,
temperature=0.7
)
return tokenizer.decode(output[0], skip_special_tokens=True)
prompt = "Write a code in react for calling api to server at https://example.com/test"
generated_text = generate_text(prompt)
print(generated_text)
|