If you use this model for own tasks, please share your results in the community tab.
With Tensorflow you can use:
from transformers import GPT2Tokenizer, TFGPT2Model
tokenizer = GPT2Tokenizer.from_pretrained("domsebalj/GPcroaT")
model = TFGPT2LMHeadModel.from_pretrained("domsebalj/GPcroaT")
text = "Zamijeni ovaj tekst vlastitim"
input_ids = tokenizer.encode(text, return_tensors='tf')
beam_output = model.generate(
input_ids,
max_length = 80,
min_length = 10,
num_beams = 10,
temperature = 5.7,
no_repeat_ngram_size=2,
num_return_sequences=5,
repetition_penalty =7.5,
length_penalty = 1.5,
top_k = 50
)
output = []
for i in beam_output:
output.append(tokenizer.decode(i))
print(output)