Kaijie Zhu

> https://archive.is/7t3it seems not available for now :(

Hi, promptbench now supports phi-2! Please clone the latest repository and use `model = pb.LLMModel(model='phi-2', max_new_tokens=10, temperature=0.001)` to load phi-2 model. Please do not hesitate to inform us for any...

Hi, promptbench now supports loading it using CPU! Please clone the latest repository and following the `examples/basic.ipynb` to try it.

Hi, could you try `dtype=torch.float32`? It works for me using the following code: `model = pb.LLMModel("phi-2", temperature=0, dtype=torch.float32, device="cpu")`

Hi Jubick, To address this issue, you can adjust the temperature setting to an extremely small value, such as temp=0.000001. This should be sufficient for the required adjustments :)

Thank you for your interest in our work! The primary objective of the attention visualization in our paper is to determine the importance of each input word in contributing to...

Hi guys, Thank you all for your interest in the visualization technique. > My scenario is like this, I have an initial prompt p, for example, a harmful jailbreak prompt,...

Hi Yihong, Thank you for your suggestions about enhancing PromptBench with DyVal integration. We appreciate your valuable suggestions and eager to discuss how we can collaborate. Could you share your...

Oh I just found in this url https://berkeley.app.box.com/s/6zt1qzwm34hgdzcvi45svsb10zspop8a, the Frost classes is correct, but in Zenodo, it is wrong.

Hi Dario, thanks for bringing this issue to us! The latest version has updated the docs.