Interestingly, we find some diversity in the lower-level semantics between the QDiffusion model and the FP models, like the heading of the horse or the shape of the hat. We leave it to future work to understand
其中KL-reg相当于在潜空间上施加了KL惩罚,使得得到的特征的分布接近正态分布。VQ-reg则是使用了一个向量量化层(vector quantization layer),向量量化层将特征归一化为码本中最近的那个特征,如图5。具体来讲,向量量化层的计算有6步: 图5:向量量化层的计算流程 特征Reshape:对于输入数据z_e \in \mathbb R^{n\...
去掉Vector-Quantization,例如 https://arxiv.org/pdf/2406.11838 当前SOTA (State of the Art) 的模型包括: Imagen3 DALLE3 Stable Diffusion3 业务使用场景 基于Diffusion的图像生成技术在多个业务场景中具有广泛的应用: 艺术创作: 生成独特的艺术作品和图案。 游戏开发: 生成游戏中的环境、角色和物品。 广告设计:...
Our approach introduces quantization scales as separable functions to consider inter-channel weight patterns. Then, it optimizes these scales in a timestep-specific manner for effective reflection of the role of each time step. TuneQDM achieves performance on par with its full-precision counterpart ...
which compresses the noise estimation network to accelerate the generation process. We identify the primary challenge of diffusion model quantization as the changing output distributions of noise estimation networks over multiple time steps and the bimodal activation distribution of the shortcut layers with...
VQGAN模型由一个编码器和一个解码器组成,其中的量化层(quantization layer)将输入图像映射成来自一个学习过的codebook的token序列。 然后完全用卷积层建立编码器和解码器,以支持对不同分辨率的图像进行编码。 编码器中包括几个下采样块来减少输入的空间维度,而解码器中则是有相应数量的上采样块来将latents映射回原始...
import torchfrom diffusers import StableDiffusion3Pipelinefrom transformers import T5EncoderModel, BitsAndBytesConfig# Make sure you have `bitsandbytes` installed.quantization_config = BitsAndBytesConfig(load_in_8bit=True)model_id = "stabilityai/stable-diffusion-3-medium-diffusers"text_encoder = T5...
024 (2023-11-27) TFMQ-DM Temporal Feature Maintenance Quantization for Diffusion Models https://arxiv.org/pdf/2311.16503.pdf 025 (2023-11-27) MagicAnimate Temporally Consistent Human Image Animation using Diffusion Model https://arxiv.org/pdf/2311.16498.pdf ...
With quantized model and full-precision model, you can collect quantization noise by: python3 quant_scripts/collect_quant_error_brecq.py Also, you can modify the amount of data you want to collect. Then you can analyze the quantization noise to get statistics (correlation, noise mean and varia...
id = "stabilityai/stable-diffusion-3.5-large"nf4_config = BitsAndBytesConfig( load_in_4bit=True, bnb_4bit_quant_type="nf4", bnb_4bit_compute_dtype=torch.bfloat16)model_nf4 = SD3Transformer2DModel.from_pretrained( model_id, subfolder="transformer", quantization_config=n...