| 模型名称 Model name | 描述 Description |
|---|---|
| AltDiffusion-m9 | Multilingual: English(En), Chinese(Zh), Spanish(Es), French(Fr), Russian(Ru), Japanese(Ja), Korean(Ko), Arabic(Ar) and Italian(It) |
| AltDiffusion | Bilingual: Chinese(Zh), English(En) |
We use AltCLIP as the text encoder, and trained a multilingual Diffusion model based on Stable Diffusion, with training data from WuDao dataset and LAION.
AltDiffusion performs well in aligning multiple languages, retaining most of the stable diffusion capabilities of the original, and in some cases even better than the original model.
AltDiffusion-m9 supports text-to-image generation for 9 different languages, which are English, Chinese, Spanish, French, Japanese, Korean, Arabic, Russian and Italian.
For the multilingual AltCLIP model, check this tutorial for more information.
Our online demo currently only supports Chinese and English. Try out it by clicking 
我们使用 AltCLIP 作为text encoder，基于 Stable Diffusion 训练了中英双语Diffusion模型(AltDiffusion)及支持9种语言的多语Diffusion模型(AltDiffusion-m9)。训练数据来自 WuDao数据集 和 LAION 。
AltDiffusion在中英文对齐方面表现非常出色，保留了原版stable diffusion的大部分能力，并且在某些例子上比有着比原版模型更出色的能力。多语言版本AltDiffusion-m9则是目前业界首个支持多语言文生图的Diffusion模型，包括对英语、中文、日语、法语、韩语、西班牙语、俄语、意大利语、阿拉伯语的支持。
AltDiffusion 模型由名为 AltCLIP 的多语 CLIP 模型支持，您可以阅读 此教程 了解更多信息。
中英文双语版模型现在支持线上演示，点击
If you find this work helpful, please consider to cite
@article{https://doi.org/10.48550/arxiv.2211.06679,
doi = {10.48550/ARXIV.2211.06679},
url = {https://arxiv.org/abs/2211.06679},
author = {Chen, Zhongzhi and Liu, Guang and Zhang, Bo-Wen and Ye, Fulong and Yang, Qinghong and Wu, Ledell},
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences},
title = {AltCLIP: Altering the Language Encoder in CLIP for Extended Language Capabilities},
publisher = {arXiv},
year = {2022},
copyright = {arXiv.org perpetual, non-exclusive license}
}
第一次运行AltDiffusion模型时会自动下载如下权重,
The following weights are automatically downloaded from when the AltDiffusion model is run for the first time:
| 模型名称 Model name | 大小 Size | 描述 Description |
|---|---|---|
| AltDiffusion | 8.0G | 我们的双语AltDiffusion模型； Our bilingual AltDiffusion model |
| AltDiffusion-m9 | 8.0G | support English(En), Chinese(Zh), Spanish(Es), French(Fr), Russian(Ru), Japanese(Ja), Korean(Ko), Arabic(Ar) and Italian(It) |
以下示例将为文本输入Anime portrait of natalie portman as an anime girl by stanley artgerm lau, wlop, rossdraws, james jean, andrei riabovitchev, marc simonetti, and sakimichan, trending on artstation 在目录./AltDiffusionOutputs下生成图片结果。
The following example will generate image results for text input Anime portrait of natalie portman as an anime girl by stanley artgerm lau, wlop, rossdraws, james jean, andrei riabovitchev, marc simonetti, and sakimichan, trending on artstation under the default output directory ./AltDiffusionOutputs
import torch
from flagai.auto_model.auto_loader import AutoLoader
from flagai.model.predictor.predictor import Predictor
# Initialize
prompt = "Anime portrait of natalie portman as an anime girl by stanley artgerm lau, wlop, rossdraws, james jean, andrei riabovitchev, marc simonetti, and sakimichan, trending on artstation"
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
loader = AutoLoader(task_name="text2img",
model_name="AltDiffusion-m9",
model_dir="./checkpoints",
use_fp16=False) # Fp16 mode
model = loader.get_model()
model.eval()
model.to(device)
predictor = Predictor(model)
predictor.predict_generate_images(prompt)您可以在predict_generate_images函数里通过改变参数来调整设置，具体信息如下:
More parameters of predict_generate_images for you to adjust for predict_generate_images are listed below:
| 参数名 Parameter | 类型 Type | 描述 Description |
|---|---|---|
| prompt | str | 提示文本; The prompt text |
| out_path | str | 输出路径; The output path to save images |
| n_samples | int | 输出图片数量; Number of images to be generate |
| skip_grid | bool | 如果为True, 会将所有图片拼接在一起，输出一张新的图片; If set to true, image gridding step will be skipped |
| ddim_step | int | DDIM模型的步数; Number of steps in ddim model |
| plms | bool | 如果为True, 则会使用plms模型; If set to true, PLMS Sampler instead of DDIM Sampler will be applied |
| scale | float | 这个值决定了文本在多大程度上影响生成的图片，值越大影响力越强; This value determines how important the prompt incluences generate images |
| H | int | 图片的高度; Height of image |
| W | int | 图片的宽度; Width of image |
| C | int | 图片的channel数; Numeber of channels of generated images |
| seed | int | 随机种子; Random seed number |
注意：模型推理要求一张至少14G以上的GPU, FP16模式下则至少11G。
Note that the model inference requires a GPU of at least 14G, and at least 11G for FP16 mode.
prompt:dark elf princess, highly detailed, d & d, fantasy, highly detailed, digital painting, trending on artstation, concept art, sharp focus, illustration, art by artgerm and greg rutkowski and fuji choko and viktoria gavrilenko and hoang lap
注: 此处长图生成技术由右脑科技(RightBrain AI)提供。
Note: The long image generation technology here is provided by Right Brain Technology.
同一句prompts不同语言生成的人脸不一样！
One prompts in different Languages generate different faces!!!
该模型通过 CreativeML Open RAIL-M license 获得许可。作者对您生成的输出不主张任何权利，您可以自由使用它们并对它们的使用负责，不得违反本许可中的规定。该许可证禁止您分享任何违反任何法律、对他人造成伤害、传播任何可能造成伤害的个人信息、传播错误信息和针对弱势群体的任何内容。您可以出于商业目的修改和使用模型，但必须包含相同使用限制的副本。有关限制的完整列表，请阅读许可证 。
The model is licensed with a CreativeML Open RAIL-M license. The authors claim no rights on the outputs you generate, you are free to use them and are accountable for their use which must not go against the provisions set in this license. The license forbids you from sharing any content that violates any laws, produce any harm to a person, disseminate any personal information that would be meant for harm, spread misinformation and target vulnerable groups. You can modify and use the model for commercial purposes, but a copy of the same use restrictions must be included. For the full list of restrictions please read the license .