# Adopted from https://github.com/huggingface/transformers/blob/main/src/transformers/models/siglip/configuration_siglip.py. | |
# Below is the original copyright: | |
# coding=utf-8 | |
# Copyright 2024 The HuggingFace Inc. team. All rights reserved. | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
"""VideoLLaMA3 vision encoder model configuration.""" | |
from transformers import PretrainedConfig | |
class Videollama3VisionEncoderConfig(PretrainedConfig): | |
model_type = "videollama3_vision_encoder" | |
def __init__( | |
self, | |
hidden_size=768, | |
intermediate_size=3072, | |
num_hidden_layers=12, | |
num_attention_heads=12, | |
num_channels=3, | |
patch_size=16, | |
hidden_act="gelu_pytorch_tanh", | |
layer_norm_eps=1e-6, | |
attention_dropout=0.0, | |
**kwargs, | |
): | |
super().__init__(**kwargs) | |
self.hidden_size = hidden_size | |
self.intermediate_size = intermediate_size | |
self.num_hidden_layers = num_hidden_layers | |
self.num_attention_heads = num_attention_heads | |
self.num_channels = num_channels | |
self.patch_size = patch_size | |
self.attention_dropout = attention_dropout | |
self.layer_norm_eps = layer_norm_eps | |
self.hidden_act = hidden_act | |