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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))
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