gpt2-finetuned-emergency

GPT-2 fine-tuned for emergency messages (Excusify)

Part of Excusify. Given a short prompt, the model writes a short, first-person urgent message for a scenario and optional details.

Prompt format

car trouble | flat tyre on the highway :

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-emergency"
tokenizer = AutoTokenizer.from_pretrained(repo)
model = AutoModelForCausalLM.from_pretrained(repo)

inputs = tokenizer("car trouble | flat tyre on the highway :", 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.