noneUsername/saiga_nemo_12b-W8A8-Dynamic-Per-Token

Consider using noneUsername/saiga_nemo_12b-W8A8-Dynamic-Per-Token-better. I tweaked the quantization parameters to get better results.

vllm (pretrained=/root/autodl-tmp/saiga_nemo_12b,add_bos_token=true,tensor_parallel_size=2,max_model_len=2048), gen_kwargs: (None), limit: 250.0, num_fewshot: 5, batch_size: auto

Tasks	Version	Filter	n-shot	Metric		Value		Stderr
gsm8k	3	flexible-extract	5	exact_match	↑	0.808	±	0.0250
		strict-match	5	exact_match	↑	0.760	±	0.0271

vllm (pretrained=/root/autodl-tmp/output,add_bos_token=true,tensor_parallel_size=2,max_model_len=2048,dtype=bfloat16), gen_kwargs: (None), limit: 250.0, num_fewshot: 5, batch_size: auto

Tasks	Version	Filter	n-shot	Metric		Value		Stderr
gsm8k	3	flexible-extract	5	exact_match	↑	0.792	±	0.0257
		strict-match	5	exact_match	↑	0.768	±	0.0268