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domsebalj/
GPcroaT

Name: GPcroaT
Availability: InStock

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With Tensorflow you can use:

python

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)