| <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, we | |
| set a seed for reproducibility: | |
| ```python | |
| >>> from transformers import pipeline, set_seed | |
| >>> generation= pipeline('text-generation', model='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 <br /> | |
| tokenizer = AutoTokenizer.from_pretrained("Tanhim/gpt2-model-de") <br /> | |
| model = AutoModelWithLMHead.from_pretrained("Tanhim/gpt2-model-de") <br /> | |
| text = "Ersetzen Sie mich durch einen beliebigen Text, den Sie wünschen." | |
| encoded_input = tokenizer(text, return_tensors='pt') | |
| output = model(**encoded_input) | |
| ``` |