readme: ---
  language: de
  widget:
  - text: Hallo, ich bin ein Sprachmodell
  
  license: gpl
  ---
  
  <h2> GPT2 Model for German Language </h2>
  
  
  Model Name: Tanhim/gpt2-model-de <br />
  language: German or Deutsch  <br />
  thumbnail: https://huggingface.co/Tanhim/gpt2-model-de <br />
  datasets: Ten Thousand German News Articles Dataset <br />
  
  ### How to use
  You can use this model directly with a pipeline for text generation. Since the generation relies on some randomness, I
  set a seed for reproducibility:
  ```python
  >>> from transformers import pipeline, set_seed
  >>> generation= pipeline('text-generation', model='Tanhim/gpt2-model-de', tokenizer='Tanhim/gpt2-model-de')
  >>> set_seed(42)
  >>> generation("Hallo, ich bin ein Sprachmodell,", max_length=30, num_return_sequences=5)
  
  ```
  Here is how to use this model to get the features of a given text in PyTorch:
  ```python
  from transformers import AutoTokenizer, AutoModelWithLMHead 
  tokenizer = AutoTokenizer.from_pretrained("Tanhim/gpt2-model-de") 
  model = AutoModelWithLMHead.from_pretrained("Tanhim/gpt2-model-de") 
  text = "Ersetzen Sie mich durch einen beliebigen Text, den Sie wünschen."
  encoded_input = tokenizer(text, return_tensors='pt')
  output = model(**encoded_input)
  ```
  
  Citation request:
  If you use the model of this repository in your research, please consider citing the following way:
  ```python
  @misc{GermanTransformer,
    author = {Tanhim Islam},
    title = {{PyTorch Based Transformer Machine Learning Model for German Text Generation Task}},
    howpublished = "\url{https://huggingface.co/Tanhim/gpt2-model-de}",
    year = {2021}, 
    note = "[Online; accessed 17-June-2021]"
  }
  ```