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add sparsevlm
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base:
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seed: &seed 42
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model:
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type: Llava
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path: model path
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torch_dtype: auto
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eval:
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eval_pos: [pretrain, transformed]
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type: vqa
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name: [mme]
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download: False
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path: MME dataset path
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bs: 1
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inference_per_block: False
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sparse:
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method: TokenReduction
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special:
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method: SparseVLM
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pruning_loc: [2] # [2, 6, 15]
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retained_tokens: 192
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init_token_total_shape: 668
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save:
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save_trans: False
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save_fake: False
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save_path: /path/to/save/
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from .base_blockwise_token_reduction import TokenReduction
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from .fastervlm import FasterVLM
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from .fastv import FastV
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from .sparsevlm import SparseVLM
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from .tome import ToMe

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