GPT-2 torch argmax issues

[quadratic]

`import torch

tokenizer_custom = GPT2Tokenizer.from_pretrained("gpt2")
model_custom = GPT2LMHeadModel.from_pretrained('gpt2')

generated_custom = tokenizer_custom.encode("The Manhattan bridge")
context_custom = torch.tensor([generated_custom])
past_custom = None

for j in range(100):
print(j)
output_custom, past_custom = model_custom(context_custom, past=past_custom)
token_custom = torch.argmax(output_custom[..., -1, :])

generated_custom += [token_custom.tolist()]
context_custom = token_custom.unsqueeze(0)
sequence_custom = tokenizer_custom.decode(generated_custom)

print(sequence_custom)`
Please help me correct this

[Muhammad Imran Zaman]

Please use this code for the text generation. make sure you have transformer and torch is installed.

pip install transformers
import torch
from transformers import GPT2Tokenizer, GPT2LMHeadModel

tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
model = GPT2LMHeadModel.from_pretrained("gpt2")
generated = tokenizer.encode("The Manhattan bridge", return_tensors='pt')
output_sequences = model.generate(
    input_ids=generated,
    max_length=150,  
    num_return_sequences=1,
    no_repeat_ngram_size=2,
    temperature=0.7,
    top_k=50,
    top_p=0.95,
    pad_token_id=tokenizer.eos_token_id
)

text = tokenizer.decode(output_sequences[0], skip_special_tokens=True)
print(text)

Note: You can fine tune the parameters for the best answer specially temperature.

[quadratic]

Thanks for the prompt reply and help let me check

[quadratic]

Its working fine and thanks for help. Although results are not promising.