I’ve been spending a lot of time with HiDream illustration LoRAs, but the last couple nights I’ve started digging into photorealistic ones. This LoRA is based on some 1980s photography and still frames from random 80s films.

After a lot of trial and error with training setup and learning to spot over/undertraining, I’m finally starting to see the style come through.

Now I’m running into what feels like a ceiling with photorealism—whether I’m using a LoRA or not. Whenever there’s anything complicated like chains, necklaces, or detailed patterns, the model seems to give up early in the diffusion process and starts hallucinating stuff.

These were made using deis/sgm_uniform with dpm_2/beta in three passes...some samplers work better than others but never as consistently as with Flux. I’ve been using that 3 pass method for a while, especially with Flux (even posted a workflow about it back then), and it usually worked great.

I know latent upscaling will always be a little unpredictable but the visual gibberish comes through even without upscaling. I feel like images need at least two passes with HiDream or they're too smooth or unfinished in general.

I’m wondering if anyone else is experimenting with photorealistic LoRA training or upscaling — are you running into the same frustrations?

Feels like I’m right on the edge of something that works and looks good, but it’s always just a bit off and I can’t figure out why. There's like an unappealing digital noise in complex patterns and textures that I'm seeing in a lot of photo styles with this model in posts from other users too. Doesn't seem like a lot of people are sharing much about training or diffusion with this one and it's a bummer because I'd really like to see this model take off.

Rubberhose Ruckus HiDream LoRA is a LyCORIS-based and trained to replicate the iconic vintage rubber hose animation style of the 1920s–1930s. With bendy limbs, bold linework, expressive poses, and clean color fills, this LoRA excels at creating mascot-quality characters with a retro charm and modern clarity. It's ideal for illustration work, concept art, and creative training data. Expect characters full of motion, personality, and visual appeal.

I recommend using the LCM sampler and Simple scheduler for best quality. Other samplers can work but may lose edge clarity or structure. The first image includes an embedded ComfyUI workflow — download it and drag it directly into your ComfyUI canvas before reporting issues. Please understand that due to time and resource constraints I can’t troubleshoot everyone's setup.

Trigger Words: rubb3rh0se, mascot, rubberhose cartoon
Recommended Sampler: LCM
Recommended Scheduler: SIMPLE
Recommended Strength: 0.5–0.6
Recommended Shift: 0.4–0.5

Areas for improvement: Text appears when not prompted for, I included some images with text thinking I could get better font styles in outputs but it introduced overtraining on text. Training for v2 will likely include some generations from this model and more focus on variety.

Training ran for 2500 steps, 2 repeats at a learning rate of 2e-4 using Simple Tuner on the main branch. The dataset was composed of 96 curated synthetic 1:1 images at 1024x1024. All training was done on an RTX 4090 24GB, and it took roughly 3 hours. Captioning was handled using Joy Caption Batch with a 128-token limit.

I trained this LoRA with Full using SimpleTuner and ran inference in ComfyUI with the Dev model, which is said to produce the most consistent results with HiDream LoRAs.

If you enjoy the results or want to support further development, please consider contributing to my KoFi: https://ko-fi.com/renderartistrenderartist.com

CivitAI: https://civitai.com/models/1551058/rubberhose-ruckus-hidream
Hugging Face: https://huggingface.co/renderartist/rubberhose-ruckus-hidream

CivitAI: https://civitai.com/models/1539779/simple-vector-hidream
Hugging Face: https://huggingface.co/renderartist/simplevectorhidream

Simple Vector HiDream LoRA is Lycoris based and trained to replicate vector art designs and styles, this LoRA leans more towards a modern and playful aesthetic rather than corporate style but it is capable of doing more than meets the eye, experiment with your prompts.

I recommend using LCM sampler with the simple scheduler, other samplers will work but not as sharp or coherent. The first image in the gallery will have an embedded workflow with a prompt example, try downloading the first image and dragging it into ComfyUI before complaining that it doesn't work. I don't have enough time to troubleshoot for everyone, sorry.

Trigger words: v3ct0r, cartoon vector art

Recommended Sampler: LCM

Recommended Scheduler: SIMPLE

Recommended Strength: 0.5-0.6

This model was trained to 2500 steps, 2 repeats with a learning rate of 4e-4 trained with Simple Tuner using the main branch. The dataset was around 148 synthetic images in total. All of the images used were 1:1 aspect ratio at 1024x1024 to fit into VRAM.

Training took around 3 hours using an RTX 4090 with 24GB VRAM, training times are on par with Flux LoRA training. Captioning was done using Joy Caption Batch with modified instructions and a token limit of 128 tokens (more than that gets truncated during training).

I trained the model with Full and ran inference in ComfyUI using the Dev model, it is said that this is the best strategy to get high quality outputs. Workflow is attached to first image in the gallery, just drag and drop into ComfyUI.

renderartist.com

Coloring Book HiDream

CivitAI: https://civitai.com/models/1518899/coloring-book-hidream
Hugging Face: https://huggingface.co/renderartist/coloringbookhidream

This HiDream LoRA is Lycoris based and produces great line art styles similar to coloring books. I found the results to be much stronger than my Coloring Book Flux LoRA. Hope this helps exemplify the quality that can be achieved with this awesome model. This is a huge win for open source as the HiDream base models are released under the MIT license.

I recommend using LCM sampler with the simple scheduler, for some reason using other samplers resulted in hallucinations that affected quality when LoRAs are utilized. Some of the images in the gallery will have prompt examples.

Trigger words: c0l0ringb00k, coloring book

Recommended Sampler: LCM

Recommended Scheduler: SIMPLE

This model was trained to 2000 steps, 2 repeats with a learning rate of 4e-4 trained with Simple Tuner using the main branch. The dataset was around 90 synthetic images in total. All of the images used were 1:1 aspect ratio at 1024x1024 to fit into VRAM.

Training took around 3 hours using an RTX 4090 with 24GB VRAM, training times are on par with Flux LoRA training. Captioning was done using Joy Caption Batch with modified instructions and a token limit of 128 tokens (more than that gets truncated during training).

The resulting LoRA can produce some really great coloring book styles with either simple designs or more intricate designs based on prompts. I'm not here to troubleshoot installation issues or field endless questions, each environment is completely different.

I trained the model with Full and ran inference in ComfyUI using the Dev model, it is said that this is the best strategy to get high quality outputs.

Spent two days tinkering with HiDream training in SimpleTuner I was able to train a LoRA with an RTX 4090 with just 24GB VRAM, around 90 images and captions no longer than 128 tokens. HiDream is a beast, I suspect we’ll be scratching our heads for months trying to understand it but the results are amazing. Sharp details and really good understanding.

I recycled my coloring book dataset for this test because it was the most difficult for me to train for SDXL and Flux, served as a good bench mark because I was familiar with over and under training.

This one is harder to train than Flux. I wanted to bash my head a few times in the process of setting everything up, but I can see it handling small details really well in my testing.

I think most people will struggle with diffusion settings, it seems more finicky than anything else I’ve used. You can use almost any sampler with the base model but when I tried to use my LoRA I found it only worked when I used the LCM sampler and simple scheduler. Anything else and it hallucinated like crazy.

Still going to keep trying some things and hopefully I can share something soon.