* 'state-spaces/mamba-130m' Returns: model: Mamba model with weights loaded """ from transformers.utils import WEIGHTS_NAME, CONFIG_NAME from transformers.utils.hub import cached_file def load_config_hf(model_name): resolved_archive_file = cached_file(model_name, CONFIG_NAME, _raise_exceptio...
lm_eval --model mamba_ssm --model_args pretrained=state-spaces/mamba-130m --tasks lambada_openai,hellaswag,piqa,arc_easy,arc_challenge,winogrande,openbookqa --device cuda --batch_size 256 python evals/lm_harness_eval.py --model hf --model_args pretrained=EleutherAI/pythia-160m --tasks ...
python evals/lm_harness_eval.py --model mamba --model_args pretrained=state-spaces/mamba-130m --tasks lambada_openai,hellaswag,piqa,arc_easy,arc_challenge,winogrande --device cuda --batch_size 64 python evals/lm_harness_eval.py --model hf --model_args pretrained=EleutherAI/pythia-160m -...
lm_eval --model mamba_ssm --model_args pretrained=state-spaces/mamba-130m --tasks lambada_openai,hellaswag,piqa,arc_easy,arc_challenge,winogrande,openbookqa --device cuda --batch_size 256 python evals/lm_harness_eval.py --model hf --model_args pretrained=EleutherAI/pythia-160m --tasks ...
lm_eval --model mamba_ssm --model_args pretrained=state-spaces/mamba-130m --tasks lambada_openai,hellaswag,piqa,arc_easy,arc_challenge,winogrande,openbookqa --device cuda --batch_size 256 python evals/lm_harness_eval.py --model hf --model_args pretrained=EleutherAI/pythia-160m --tasks ...
7.5 RLHF 与物理推理奖励优化 8. 结论 1. 引言 本文提出了Cosmos-Reason1系列多模态大语言模型,专注于提升物理人工智能(Physical AI)系统在物理常识(Physical Common Sense)与具身推理(Embodied Reasoning)方面的能力。模型能够通过对视频等视觉输入的理解,结合长链式思维(Chain-of-Thought, CoT)过程,在自然语言中做...
lm_eval --model mamba_ssm --model_args pretrained=state-spaces/mamba-130m --tasks lambada_openai,hellaswag,piqa,arc_easy,arc_challenge,winogrande,openbookqa --device cuda --batch_size 256 python evals/lm_harness_eval.py --model hf --model_args pretrained=EleutherAI/pythia-160m --tasks ...
lm_eval --model mamba_ssm --model_args pretrained=state-spaces/mamba-130m --tasks lambada_openai,hellaswag,piqa,arc_easy,arc_challenge,winogrande,openbookqa --device cuda --batch_size 256 python evals/lm_harness_eval.py --model hf --model_args pretrained=EleutherAI/pythia-160m --tasks ...
lm_eval --model mamba_ssm --model_args pretrained=state-spaces/mamba-130m --tasks lambada_openai,hellaswag,piqa,arc_easy,arc_challenge,winogrande,openbookqa --device cuda --batch_size 256 python evals/lm_harness_eval.py --model hf --model_args pretrained=EleutherAI/pythia-160m --tasks ...
lm_eval --model mamba_ssm --model_args pretrained=state-spaces/mamba-130m --tasks lambada_openai,hellaswag,piqa,arc_easy,arc_challenge,winogrande,openbookqa --device cuda --batch_size 256 python evals/lm_harness_eval.py --model hf --model_args pretrained=EleutherAI/pythia-160m --tasks ...