What is this?

A fine-tuned GPT-2 model (small version, 124 M parameters) for generating responses to customer reviews in Danish.

How to use

The model is based on the gpt2-small-danish model. 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 to train (see the example below).

Test the model using the pipeline from the 🤗 Transformers library:

from transformers import pipeline

generator = pipeline("text-generation", model = "KennethTM/gpt2-small-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:

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("KennethTM/gpt2-small-danish-review-response")
model = AutoModelForCausalLM.from_pretrained("KennethTM/gpt2-small-danish-review-response")

Notes

The model may get the sentiment of the review wrong resulting in a mismatch between the review and response. The model would probably benefit from sentiment tuning.