Text-to-Image
Diffusers
Safetensors
diffusion
flow-matching
lora
nitro-e
wikiart
art
emotiongoes
more-art-than-science
Instructions to use emotiongoes/nitro-e-wikiart with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use emotiongoes/nitro-e-wikiart with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("amd/Nitro-E", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("emotiongoes/nitro-e-wikiart") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update README.md
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README.md
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# Nitro-E · WikiArt Themes & Feelings (EMA-aligned)
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A LoRA post-training of **[amd/Nitro-E](https://huggingface.co/amd/Nitro-E)** (304M E-MMDiT,
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flow-matching, MIT) that renders subjects in fine-art styles conditioned on
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(`nitro_cc_ema_merged.safetensors`) plus the LoRA adapter it was merged from.
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The **EMA** (exponential moving average over the LoRA weights, rate 0.9999) is the key fix:
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a rank-16 LoRA on ~29k images overfits within a couple thousand steps and the raw weights
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collapse to noise past the knee; the EMA-averaged weights stay coherent. This is the
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checkpoint served in the live demo.
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- **Base:** `amd/Nitro-E` (Nitro-E-512px), text encoder `meta-llama/Llama-3.2-1B` (gated), VAE `mit-han-lab/dc-ae-f32c32-sana-1.0`.
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- **Resolution:** 512x512. **License:** MIT (base) — see data notes below.
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- **Tracking:** [https://wandb.ai/imaging-ai/more-art-than-science](https://wandb.ai/imaging-ai/more-art-than-science)
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- `adapter_config.json` + `adapter_model.safetensors` — the PEFT LoRA adapter (apply on top of `amd/Nitro-E` if you prefer not to use the merged weights).
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## Training data
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— 32,061 WikiArt works (metadata + image URLs). ~29,000 images were downloadable and
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used. The `consolidated-caption` field carries the emotional/style signal used as the prompt.
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## Recipe
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- Inherits Nitro-E 304M quality ceiling; can overfit WikiArt style cues.
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- Requires gated `meta-llama/Llama-3.2-1B` access to run.
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- **Data rights:** trained on WikiArt images but does not redistribute them; the dataset is
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metadata-only. Many works are public domain but not all
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# Nitro-E · WikiArt Themes & Feelings (EMA-aligned)
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A LoRA post-training of **[amd/Nitro-E](https://huggingface.co/amd/Nitro-E)** (304M E-MMDiT,
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flow-matching, MIT) from AMD Brain that renders subjects in fine-art styles conditioned on art movement, genre, emotion and theme.
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This repo holds the EMA-aligned, merged, serveable checkpoint
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(`nitro_cc_ema_merged.safetensors`) plus the LoRA adapter it was merged from.
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- **Base:** `amd/Nitro-E` (Nitro-E-512px), text encoder `meta-llama/Llama-3.2-1B` (gated), VAE `mit-han-lab/dc-ae-f32c32-sana-1.0`.
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- **Resolution:** 512x512. **License:** MIT (base) — see data notes below.
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- **Tracking:** [https://wandb.ai/imaging-ai/more-art-than-science](https://wandb.ai/imaging-ai/more-art-than-science)
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- `adapter_config.json` + `adapter_model.safetensors` — the PEFT LoRA adapter (apply on top of `amd/Nitro-E` if you prefer not to use the merged weights).
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## Training data
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— A private dataset of 32,061 WikiArt works (metadata + image URLs). ~29,000 images were downloadable and
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used. The `consolidated-caption` field carries the emotional/style signal used as the prompt.
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## Recipe
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- Inherits Nitro-E 304M quality ceiling; can overfit WikiArt style cues.
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- Requires gated `meta-llama/Llama-3.2-1B` access to run.
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- **Data rights:** trained on WikiArt images but does not redistribute them; the dataset is
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metadata-only. Many works are public domain but not all so use outputs accordingly.
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