gpt2-finetuned-apologies

GPT-2 fine-tuned for apologies (Excusify)

Part of Excusify. Given a short prompt, the model writes an apology for a situation in an emotional, professional or informal tone.

Prompt format

professional | being late to the meeting :

The model writes the completion after the colon and stops with an end-of-text token.

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

repo = "Sohamb2005/gpt2-finetuned-apologies"
tokenizer = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(repo)

inputs = tokenizer("professional | being late to the meeting :", return_tensors="pt")
out = model.generate(**inputs, do_sample=True, top_p=0.92, temperature=0.8, max_new_tokens=60,
                     pad_token_id=tokenizer.eos_token_id)
print(tokenizer.decode(out[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))

Training

Evaluation

Situation match is the share of sampled answers that mention at least one content word of the situation in the prompt.

Limitations

Made for entertainment and practice messages. The training set is small and hand-written, so the model can repeat phrasings from it, and situations far from the training data may get generic answers.