Instructions to use tm-hf-repo/seedream-pixar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tm-hf-repo/seedream-pixar with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("undefined", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("tm-hf-repo/seedream-pixar") prompt = "tmc_pix" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
seedream pixar
Model description
This is a 3000 step flux kontext lora trained on the seedream prompt:
convert this to a 3d pixar style, maintain the same pose, colors, skin tone, and hair. beautiful 3d rendered hair texture, empty white background
Trigger words
You should use tmc_pix to trigger the image generation.
Recommendations:
- Try increasing the steps to 40 during generation and guidance scale to 3-3.5
- Highly recommend adding "maintain the same skin tone" to the "tmc_pix" prompt
- Note due to the training data, it pretty much always skews towards smiling, seedream pixar seems to overfit to smiling characters
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Training at fal.ai
Training was done using fal.ai/models/fal-ai/flux-kontext-trainer.
INPUT IMAGE
Base output at seed=42 and prompt="tmc_pix" everything else defaults
Base output at seed=42, guidance=3.5, prompt="tmc-pix, maintain the same skin tone",
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