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---
language:
- da
pipeline_tag: text-generation
widget:
- text: "### Bruger:\nAnders\n\n### Anmeldelse:\nUmuligt at komme igennem på telefonen.\n\n### Svar:\nKære Anders\n"
---
# What is this?
A fine-tuned GPT-2 model (medium version, ~354.8 M parameters) for generating responses to customer reviews in Danish.
# How to use
The model is based on the [gpt2-medium-danish model](https://huggingface.co/KennethTM/gpt2-medium-danish) and performs better than the smaller version ([gpt2-small-danish-review-response](https://huggingface.co/KennethTM/gpt2-small-danish-review-response)). Supervised fine-tuning is applied to adapt the model to generate responses to customer reviews in Danish. A prompting template is applied to the examples used for training (see the example below).
Test the model using the pipeline from the [🤗 Transformers](https://github.com/huggingface/transformers) library:
```python
from transformers import pipeline
generator = pipeline("text-generation", model = "KennethTM/gpt2-medium-danish-review-response")
def prompt_template(user, review):
return f"### Bruger:\n{user}\n\n### Anmeldelse:\n{review}\n\n### Svar:\nKære {user}\n"
prompt = prompt_template(user = "Anders", review = "Umuligt at komme igennem på telefonen.")
text = generator(prompt)
print(text[0]["generated_text"])
```
Or load it using the Auto* classes:
```python
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("KennethTM/gpt2-medium-danish-review-response")
model = AutoModelForCausalLM.from_pretrained("KennethTM/gpt2-medium-danish-review-response")
``` |