tags:
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
- fluxgym
widget:
- output:
url: sample/cboyardee-dilbert-video-style_005100_00_20240917161546.png
text: cboyardee_dilbert a cartoon of a man drinking coffee in an office
- output:
url: sample/cboyardee-dilbert-video-style_005100_01_20240917161556.png
text: cboyardee_dilbert a cartoon of a happy dog
- output:
url: sample/cboyardee-dilbert-video-style_005100_02_20240917161606.png
text: cboyardee_dilbert a cartoon of a mcdonalds restaurant exterior
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: cboyardee_dilbert
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
cboyardee-dilbert-video-style
A Flux LoRA trained on an NVIDIA 4070 Ti Super with Fluxgym. This is a style transfer LoRA designed to replicate the unique MSPaint style of cboyardee's artwork.
Dataset is a collection of 32 frames extracted and cropped from this video, tagged with Florence-2 with some manual changes. 16 epochs were used with 10 repeat trains per image, resulting in a total step count of 5120.
- Prompt
- cboyardee_dilbert a cartoon of a man drinking coffee in an office
- Prompt
- cboyardee_dilbert a cartoon of a happy dog
- Prompt
- cboyardee_dilbert a cartoon of a mcdonalds restaurant exterior
Trigger words
You should use cboyardee_dilbert to trigger the image generation.
All tags began with "a cartoon of" but it seems like omitting that prefix still results in good outputs. In the future I want to retag with "MSPaint drawing" as it more accurately describes the style.
Note that "Dilbert" (or other characters) were not used in tagging, and so the LoRA will not be able to reproduce the character.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, Forge, etc.
Weights for this model are available in Safetensors format.
The main safetensors file achieves good outputs, but partial saves are also included with the number of epochs: 4, 8, 12. These files can be ignored unless you want to experiment with fewer-step models.