Datasets:
| import torch | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| BASE_MODEL = "meta-llama/Meta-Llama-3-8B" | |
| prompt = "ශ්රී ලංකාවේ අධ්යාපන පද්ධතිය ගැන කෙටියෙන් පැහැදිලි කරන්න." | |
| tok = AutoTokenizer.from_pretrained(BASE_MODEL, use_fast=True) | |
| if tok.pad_token is None: | |
| tok.pad_token = tok.eos_token | |
| model = AutoModelForCausalLM.from_pretrained( | |
| BASE_MODEL, | |
| torch_dtype=torch.float16, | |
| device_map="auto" | |
| ) | |
| inputs = tok(prompt, return_tensors="pt").to(model.device) | |
| with torch.no_grad(): | |
| out = model.generate( | |
| **inputs, | |
| max_new_tokens=150, | |
| temperature=0.7, | |
| top_p=0.9, | |
| do_sample=True, | |
| pad_token_id=tok.eos_token_id, | |
| ) | |
| print(tok.decode(out[0], skip_special_tokens=True)) | |