File size: 2,457 Bytes
35e4140 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | # Copyright 2025-2026 The Moonshot AI Team and HuggingFace Inc. team. All rights reserved.
#
# Extracted from moonshotai/Kimi-K3 for standalone MoonViT-V2 use.
# Licensed under the Kimi K3 License (see LICENSE in this repository).
from transformers.configuration_utils import PretrainedConfig
class MoonViTV2Config(PretrainedConfig):
r"""
Configuration class for MoonViT-V2, the native-resolution vision encoder of Kimi K3.
MoonViT-V2 is a ~0.4B-parameter Vision Transformer (27 layers, 12 heads, patch size 14)
trained from scratch jointly with the language model (not initialized from SigLIP).
"""
model_type = "moonvit_v2"
def __init__(
self,
patch_size: int = 14,
init_pos_emb_height: int = 64,
init_pos_emb_width: int = 64,
init_pos_emb_time: int = 4,
pos_emb_type: str = "divided_fixed",
pos_emb_interpolation_mode: str = "bilinear",
num_attention_heads: int = 12,
num_hidden_layers: int = 27,
hidden_size: int = 1024,
intermediate_size: int = 4096,
qkv_hidden_size: int = 1536,
merge_kernel_size: tuple[int, int] = (2, 2),
merge_type: str = "sd2_tpool",
norm_type: str = "rmsnorm",
mlp_type: str = "mlp2",
attn_bias: bool = False,
linear_bias: bool = False,
patch_embed_proj_bias: bool = False,
activation_func: str = "gelu_pytorch_tanh",
**kwargs,
):
super().__init__(**kwargs)
self.patch_size = patch_size
self.init_pos_emb_height = init_pos_emb_height
self.init_pos_emb_width = init_pos_emb_width
self.init_pos_emb_time = init_pos_emb_time
self.pos_emb_type = pos_emb_type
self.pos_emb_interpolation_mode = pos_emb_interpolation_mode
self.num_attention_heads = num_attention_heads
self.num_hidden_layers = num_hidden_layers
self.hidden_size = hidden_size
self.intermediate_size = intermediate_size
self.qkv_hidden_size = qkv_hidden_size
self.merge_kernel_size = list(merge_kernel_size) if not isinstance(merge_kernel_size, list) else merge_kernel_size
self.merge_type = merge_type
self.norm_type = norm_type
self.mlp_type = mlp_type
self.attn_bias = attn_bias
self.linear_bias = linear_bias
self.patch_embed_proj_bias = patch_embed_proj_bias
self.activation_func = activation_func
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