minisoul

1.Load Weight

import torch
from llms_from_scratch.ch04 import GPTModel
# For llms_from_scratch installation instructions, see:
# https://github.com/rasbt/LLMs-from-scratch/tree/main/pkg

BASE_CONFIG = {
    "vocab_size": 50257,    # Vocabulary size
    "context_length": 1024, # Context length
    "drop_rate": 0.0,       # Dropout rate
    "qkv_bias": True        # Query-key-value bias
}


gpt = GPTModel(BASE_CONFIG)
gpt.load_state_dict(torch.load(file_name, weights_only=True))
gpt.eval()

device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
gpt.to(device);

2. Generate Text

import tiktoken
from llms_from_scratch.ch05 import generate, text_to_token_ids, token_ids_to_text


torch.manual_seed(123)

tokenizer = tiktoken.get_encoding("gpt2")

token_ids = generate(
    model=gpt.to(device),
    idx=text_to_token_ids("Every effort moves", tokenizer).to(device),
    max_new_tokens=30,
    context_size=BASE_CONFIG["context_length"],
    top_k=1,
    temperature=1.0
)

print("Output text:\n", token_ids_to_text(token_ids, tokenizer))