\begin{table*}[htp]
\resizebox{\textwidth}{!}{
\begin{tabular}{lrrrrrr}
\toprule
Model/adapter & LM Evaluated Safety score & # eval & # train & truncated & # prompt tokens & # output tokens \\
\midrule
DBRX Instruct & 0.815 & 100.0 &  &  & 10.48 & 265.12 \\
DeepSeek LLM Chat (67B) & 0.885 & 100.0 &  &  & 10.81 & 133.02 \\
Llama 3 Instruct (70B) & 0.985 & 100.0 &  &  & 10.48 & 250.05 \\
Llama 3 Instruct (8B) & 0.9675 & 100.0 &  &  & 10.48 & 232.85 \\
Llama 3.1 Instruct Turbo (405B) & 0.965 & 100.0 &  &  & 10.48 & 235.92 \\
Llama 3.1 Instruct Turbo (70B) & 0.9875 & 100.0 &  &  & 10.48 & 243.58 \\
Llama 3.1 Instruct Turbo (8B) & 0.9425 & 100.0 &  &  & 10.48 & 236.43 \\
Mistral Instruct v0.3 (7B) & 0.9425 & 100.0 &  &  & 11.39 & 251.74 \\
Mixtral Instruct (8x22B) & 0.96 & 100.0 &  &  & 11.39 & 221.44 \\
Qwen1.5 Chat (72B) & 0.96 & 100.0 &  &  & 10.48 & 245.42 \\
Qwen2 Instruct (72B) & 0.97 & 100.0 &  &  & 10.48 & 233.49 \\
Claude 3 Haiku (20240307) & 0.855 & 100.0 &  &  & 10.69 & 130.54 \\
Claude 3 Sonnet (20240229) & 0.85 & 100.0 &  &  & 10.69 & 121.0 \\
Claude 3 Opus (20240229) & 0.9425 & 100.0 &  &  & 10.69 & 156.44 \\
Claude 3.5 Sonnet (20240620) & 0.97 & 100.0 &  &  & 10.69 & 162.97 \\
Command R & 0.9625 & 100.0 &  &  & 10.22 &  \\
Command R Plus & 0.9525 & 100.0 &  &  & 10.22 &  \\
GPT-3.5 Turbo (0613) & 0.9425 & 100.0 &  &  & 10.48 & 162.99 \\
GPT-3.5 Turbo (1106) & 0.93 & 100.0 &  &  & 10.48 & 95.83 \\
GPT-3.5 Turbo (0125) & 0.9525 & 100.0 &  &  & 10.48 & 116.12 \\
GPT-4 Turbo (2024-04-09) & 0.99 & 100.0 &  &  & 10.48 & 235.89 \\
GPT-4o (2024-05-13) & 0.985 & 100.0 &  &  & 10.42 & 231.54 \\
\bottomrule
\end{tabular}}
\caption{Results for xstest_ (xstest)}
\label{fig:xstest_ (xstest)}
\end{table*}