metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: >-
capybara hf, A cartoon drawing of a brown bear sitting in front of a
laptop. The bear is facing to the right and has a smiley face on the
screen of the laptop. Above the bear is a white bear with a black nose and
a black mouth. The background is a light beige color.
output:
url: images/C1.png
- text: >-
capybara hf, A cartoon drawing of a brown bear wearing sunglasses with a
yellow circle at the top of the eyes. The bears eyes are tinted black, and
the bears body is a light brown color. He is holding a pink money in his
right hand. The money has a black border around it, and there are two
yellow smiley faces on the eyes of the bear. The background is a solid
white color.
output:
url: images/C2.png
- text: >-
capybara hf, A cartoon drawing of a brown bear with a black hat on its
head. The bear is wearing a black shirt with a pink collar. The bears face
is brown and the bears mouth is black. There is a smiley face in the
bottom right corner of the image. There are white clouds in the
background.
output:
url: images/C3.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: capybara hf
license: apache-2.0
Flux-Super-Capybara-HF
The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.
Model description
prithivMLmods/Flux-Super-Capybara-HF
Image Processing Parameters
Parameter | Value | Parameter | Value |
---|---|---|---|
LR Scheduler | constant | Noise Offset | 0.03 |
Optimizer | AdamW | Multires Noise Discount | 0.1 |
Network Dim | 64 | Multires Noise Iterations | 10 |
Network Alpha | 32 | Repeat & Steps | 22 & 2900 |
Epoch | 15 | Save Every N Epochs | 1 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 20
Best Dimensions
- 768 x 1024 (Best)
- 1024 x 1024 (Default)
Setting Up
import torch
from pipelines import DiffusionPipeline
base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)
lora_repo = "strangerzonehf/Flux-Super-Capybara-HF"
trigger_word = "capybara hf"
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
Trigger words
You should use capybara hf
to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.