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Running
on
Zero
Running
on
Zero
from transformers import PretrainedConfig | |
class LlavaConfig(PretrainedConfig): | |
model_type = "llava" | |
def __init__( | |
self, | |
llm_cfg=None, | |
vision_tower_cfg=None, | |
mm_projector_cfg=None, | |
mask_encoder_cfg=None, | |
context_provider_cfg=None, | |
architectures=None, | |
resume_path=None, | |
hidden_size=None, | |
mm_hidden_size=None, | |
image_aspect_ratio=None, | |
num_video_frames=None, | |
mm_vision_select_layer=None, | |
mm_vision_select_feature=None, | |
mm_use_im_start_end=False, | |
mm_use_im_patch_token=True, | |
mm_projector_lr=None, | |
vision_resolution=None, | |
interpolate_mode=None, | |
s2=None, | |
s2_scales=None, | |
s2_max_split_size=None, | |
**kwargs | |
): | |
super().__init__() | |
self.architectures = architectures | |
self.llm_cfg = llm_cfg | |
self.vision_tower_cfg = vision_tower_cfg | |
self.mm_projector_cfg = mm_projector_cfg | |
self.mask_encoder_cfg = mask_encoder_cfg | |
self.context_provider_cfg = context_provider_cfg | |
self.resume_path = resume_path | |
self.hidden_size = hidden_size | |
self.mm_hidden_size = mm_hidden_size | |
self.image_aspect_ratio = image_aspect_ratio | |
self.num_video_frames = num_video_frames | |
self.mm_vision_select_layer = mm_vision_select_layer | |
self.mm_vision_select_feature = mm_vision_select_feature | |
self.mm_use_im_start_end = mm_use_im_start_end | |
self.mm_use_im_start_end = mm_use_im_start_end | |
self.mm_use_im_patch_token = mm_use_im_patch_token | |
self.mm_projector_lr = mm_projector_lr | |
self.vision_resolution = vision_resolution | |
self.interpolate_mode = interpolate_mode | |
self.s2 = s2 | |
self.s2_scales = s2_scales | |
self.s2_max_split_size = s2_max_split_size | |