NewBie image Exp0.1

🧱 Exp0.1 Base
NewBie image Exp0.1 is a 3.5B parameter DiT model developed through research on the Lumina architecture.
Building on these insights, it adopts Next-DiT as the foundation to design a new NewBie architecture tailored for text-to-image generation.
The NewBie image Exp0.1 model is trained within this newly constructed system, representing the first experimental release of the NewBie text-to-image generation framework.
Text Encoders
We use Gemma3-4B-it as the primary text encoder, conditioning on its penultimate-layer token hidden states. We also extract pooled text features from Jina CLIP v2, project them, and fuse them into the time/AdaLN conditioning pathway. Together, Gemma3-4B-it and Jina CLIP v2 provide strong prompt understanding and improved instruction adherence.
VAE
Use the FLUX.1-dev 16channel VAE to encode images into latents, delivering richer, smoother color rendering and finer texture detail helping safeguard the stunning visual quality of NewBie image Exp0.1.
Prompt
XML structured prompt
Natural language prompt
Tag prompt
🖼️ Task type
NewBie image Exp0.1 is pretrain on a large corpus of high-quality anime data, enabling the model to generate remarkably detailed and visually striking anime style images.
We reformatted the dataset text into an XML structured format for our experiments. Empirically, this improved attention binding and attribute/element disentanglement, and also led to faster convergence.
Besides that, It also supports natural language and tags inputs.
🧰 Model Zoo
NewBie image Exp0.1: Hugging face | modelscope
Gemma3-4B-it: Hugging face | modelscope
Jina CLIP v2: Hugging face | modelscope
FLUX.1-dev VAE: Hugging face | modelscope
💪 Training procedure

🔬 Participate
Core
Members
✨ Acknowledgments
Thanks to the Alpha-VLLM Org for open sourcing the advanced Lumina family. which has been invaluable for our research.
Thanks to Google for open sourcing the powerful Gemma3 LLM family
Thanks to the Jina AI Org for open sourcing the Jina family, enabling further research.
Thanks to Black Forest Labs for open sourcing the FLUX VAE family. powerful 16channel VAE is one of the key components behind improved image quality.
Thanks to Neta.art for fine-tuning and open sourcing the Lumina-image-2.0 base model. Neta-Lumina gives us the opportunity to study the performance of Next-DiT on Anime Types.
Thanks to DeepGHS/narugo1992/SumomoLee for providing high-quality Anime Datasets.
Thanks to Nyanko for the early help and support.
Thanks to woctordho for helping improve NewBie’s compatibility with community tools.
📖 Contribute
Neko, 衡鲍, XiaoLxl, xChenNing, Hapless, Lius
WindySea, 秋麒麟热茶, 古柯, Rnglg2, Ly, GHOSTLXH
Sarara, Seina, KKT机器人, NoirAlmondL, 天满, 暂时
Wenaka喵, ZhiHu, BounDless, DetaDT, 紫影のソナーニル
花火流光, R3DeK, 圣人A, 王王玉, 乾坤君Sennke, 砚青
Heathcliff01, 无音, MonitaChan, WhyPing, TangRenLan
HomemDesgraca, EPIC, ARKBIRD, Talan, 448, Hugs288
🧭 Community Guide
Getting Started Guide
LoRa Trainer
💬 Communication
📜 License
Model Weights: Newbie Non-Commercial Community License (Newbie-NC-1.0).
Applies to: model weights/parameters/configs and derivatives (fine-tunes, LoRA, merges, quantized variants, etc.)
For Non Commercial use only, and must be shared under the same license.
Code: Apache License 2.0.
Applies to: training/inference scripts and related source code in this project.
See Apache-2.0
⚠️ Disclaimer
This model may produce unexpected or harmful outputs. Users are solely responsible for any risks and potential consequences arising from its use.
Description
This is an earlier version prior to data augmentation. While it offers superior aesthetics and abstract expression with more stable limb generation compared to Exp0.1 Base its primary drawbacks are a limited knowledge base and lower conceptual fit.
FAQ
Comments (37)
来支持了
(mega宝石海星奔跑)
Why OeAi has been removed?
this model has any quantized gguf versions?
This model was a bit more difficult to use, compared to SDXL-based ones. But here's what I found out:
1. You can use normal tags like you're used to, but XML formatting gives you actual control of the image.
2. You can use this model in ComfyUI (remember to update!). You don't need to download another version of Comfy or anything like that. Just in DualCLIPLoader select type: newbie.
3. I'm not sure how to get pleasingly looking images this model. Probably because it's a base. Haven't tried LoRAs yet.
4. Don't expect this model to be fast. It's comparable to Z-Image Turbo at CFG=1.0 for it/s. But I think the trade-off is worth it for being able to exactly prompt how the image will look like.
5. FP8 will kill quality drastically but increase speed. I think it's better to wait with FP16. Just use TorchCompileModelAdvanced from KJNodes.
Could you link or upload a workflow that uses the DualClipLoader node? I can't seem to get the newbie clip loader one to work and the official comfyui newbie workflow doesn't seem to use it either
@Baxter Yeah, sure: https://media.discordapp.net/attachments/1394827694629326959/1457688537687134350/ComfyUI_temp_nqrop_00027_.png?ex=695d927d&is=695c40fd&hm=b2baf10e6df4c8e2314440587f811d6b7d7198e3b79508f68724120b39cf04c3&=&format=webp&quality=lossless&width=949&height=949
This one also includes TorchCompileModelAdvanced from KJNodes, but you can delete that if you don't need it.
Newbie is very slow and hard to prompt for good images. Neta Lumina is easier :c
@simadude The URL will be expired in a few days
Unable to find workflow in ComfyUI_temp_nqrop_00027_.webp
Might take months before civitai decides to add the NewBie/Next model category
Why on earth does it take them so long?
The quality of the images is really poor, and I don't understand why they're all crooked, distorted, and so on. all the custom illustrious models a re better out of the box. I understand that this is a 0.1 model, but I still expected more.
make sure you prompt with xml format
NetaLumina is easier, but needs better support anyway
I think not,this model is potential
@Mostima out of the box, either everything looks very crooked, or the image looks like a "draft" of very rough work. as an ordinary user who is not so well versed in all this internal structure and everything else - so far it does not look very good. There may be something else that needs to be done additionally, but I just don't understand and don't know what the problem might be. Because I see that people have good-looking options.
I am having the same results, the images other people are getting look amazing though. I think we're both doing something wrong, I tried the workflow that is inside ComfyUI and another one on CivitAI same result
非常好ep7,没有掺入e621的狗屎
没必要这么说话吧,好歹尊重一下啊
@qek 把这坨东西塞进模型里是纯粹的负面效果,365k之后塞入了e621导致模型美学水平和出图质量出现了显著退步
什么时候出个NSFW版本的呀,我觉得社区可能更需要这个(笑)
这个模型本身就支持nsfw吧
Its kinda sad that the lack of a CivitAI category is killing the inital hype for this model. This is genuinely the single best anime-themed model in the open source market. Lets hope CivitAI gives it a category soon so more people can take notice...
Really cool idea, but I really hate XML and it's quite confusing. This could be simplified with a custom ComfyUI node that just puts everything in a text box and outputs the right XML e.g.
gender:
[textbox here]
appearance:
[textbox here]
...
There is also other markdown formats outside of XML like JSON of course sure you know that one, but also TOML, YAML, if you make another model please consider
When will web UI support be available?
Still learning... The issue with BF16 is that you basically can't run it on old architectures unless you're willing to endure the snail's pace of FP32. The model seems like a good one—at least it has a lot of potential—but the problem is that it's far too dependent on prompt engineering. As someone who can't draw, I've been trying to learn how to write prompts, only to realize that in the time I've spent doing that, I could have actually learned the basics of hand-drawing. Regardless, I appreciate the developers' hard work. It's a very promising architecture, and I’m looking forward to future developments. Also, I'm waiting for an FP16 version.
请问这个 xml 格式的提示词,要怎么调整部分提示词的权重,我常用的画师串要改权重来着,入门文档没讲……
和sd一样,直接括号数字即可
不知为什么最右边会出现一条红线🤔
权重对0点几的支持不好,尽量避免
@Creeper_MZ 好的,想问问这个数据到什么时候呢,还有要保留下划线吗
@Done_shark 25年10月,保留下划线
is there any way to run this model on the ROCm comfy version?...






