readme: ---
  tags:
  - generated_from_keras_callback
  model-index:
  - name: tmpq0jhm_jh
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information Keras had access to. You should
  probably proofread and complete it, then remove this comment. -->
  
  ## Model description
  
  This is a gpt2 model trained on 142 612 different Lithuanian Wikipedia articles + 11 405 articles taken from delfi.lt, ve.lt and respublika.lt news portals.
  
  ## Intended uses & limitations
  
  This is a model I trained when writing my bachelors. You can use it anywhere you want.
  
  ### Training results
  
  Model reached 36.83% accuracy with training data and 37.02% with validation data
  
  ### Framework versions
  
   Transformers 3.5.0
   TensorFlow 2.4.1
   Tokenizers 0.12.1
   Torch 1.4.0
  
  How to use it:
  
  ```python
  import tensorflow as tf
  from transformers import WEIGHTS_NAME, CONFIG_NAME
  from transformers import GPT2Config, TFGPT2LMHeadModel, GPT2Tokenizer
  import os
  output_dir = '...' #local file or link to this page
  tokenizer = GPT2Tokenizer.from_pretrained(output_dir)
  model = TFGPT2LMHeadModel.from_pretrained(output_dir)
  
  text = "Siekdamas"
  # encoding the input text
  input_ids = tokenizer.encode(text, return_tensors='tf')
  # getting out output
  beam_outputs = model.generate(
    input_ids,
    max_length = 150,
    num_beams = 5,
    temperature = 0.7,
    no_repeat_ngram_size=2,
    num_return_sequences=5
  )
  
  print(tokenizer.decode(beam_outputs[0]))
  ```