61
stars
13
commits
Python
primary language
Mar 12, 2025
updated
Link to paper: https://arxiv.org/abs/2405.15012
To install requirements:
# download the dataset and models
wget "https://zenodo.org/records/12759549/files/prompt2output_inverters.zip?download=1" -O prompt2output_inverters.zip
wget "https://zenodo.org/records/12759549/files/prompt2output_datasets.zip?download=1" -O prompt2output_datasets.zip
unzip prompt2output_inverters.zip
unzip prompt2output_datasets.zip
pip install .
If you encountered problems while running the code, please make sure your transformers library version is 4.36.0, if it is too new, there will be problem
If you want to use this model to extract prompt of a GPTs (LLM app). You can ask these questions to the GPTs:
With these four questions, you can get 64 outputs from the GPTs.
See prompt_outputs in main.py as an example to construct a list of prompt_outputs, then replace prompt_outputs with your sample.
Then run python main.py test_sample to get the result.
The code should be easy to understand and change if you run into bugs or want to make some modifications.
To train the model(s) in the paper, run this command:
# system prompts
python main.py train system_prompts synthetic
# user prompts
python main.py train user_prompts synthetic
inverters
user_prompts
system_prompts
user prompts dataset
chat_instruction2m
lm_instruction2m
sharegpt
unnatural
system prompts dataset
synthetic
real
awesome
To evalute my model on the datasets, run
# system prompts
python main.py test system_prompts synthetic
python main.py test system_prompts real
python main.py test system_prompts awesome
# user prompts
python main.py test user_prompts chat_instruction2m
python main.py test user_prompts sharegpt
python main.py test user_prompts unnatural
# test on single sample
python main.py test_sample
The pre-trained models are in the inverters folder
13 commits
Python
100.0%
61
stars
13
commits
Python
primary language
Mar 12, 2025
updated
Link to paper: https://arxiv.org/abs/2405.15012
To install requirements:
# download the dataset and models
wget "https://zenodo.org/records/12759549/files/prompt2output_inverters.zip?download=1" -O prompt2output_inverters.zip
wget "https://zenodo.org/records/12759549/files/prompt2output_datasets.zip?download=1" -O prompt2output_datasets.zip
unzip prompt2output_inverters.zip
unzip prompt2output_datasets.zip
pip install .
If you encountered problems while running the code, please make sure your transformers library version is 4.36.0, if it is too new, there will be problem
If you want to use this model to extract prompt of a GPTs (LLM app). You can ask these questions to the GPTs:
With these four questions, you can get 64 outputs from the GPTs.
See prompt_outputs in main.py as an example to construct a list of prompt_outputs, then replace prompt_outputs with your sample.
Then run python main.py test_sample to get the result.
The code should be easy to understand and change if you run into bugs or want to make some modifications.
To train the model(s) in the paper, run this command:
# system prompts
python main.py train system_prompts synthetic
# user prompts
python main.py train user_prompts synthetic
inverters
user_prompts
system_prompts
user prompts dataset
chat_instruction2m
lm_instruction2m
sharegpt
unnatural
system prompts dataset
synthetic
real
awesome
To evalute my model on the datasets, run
# system prompts
python main.py test system_prompts synthetic
python main.py test system_prompts real
python main.py test system_prompts awesome
# user prompts
python main.py test user_prompts chat_instruction2m
python main.py test user_prompts sharegpt
python main.py test user_prompts unnatural
# test on single sample
python main.py test_sample
The pre-trained models are in the inverters folder
13 commits
Python
100.0%