The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.
prithivMLmods/Canopus-Snoopy-Charlie-Brown-Flux-LoRA
Image Processing Parameters
| Parameter | Value | Parameter | Value |
|---|---|---|---|
| LR Scheduler | constant | Noise Offset | 0.03 |
| Optimizer | AdamW8bit | Multires Noise Discount | 0.1 |
| Network Dim | 64 | Multires Noise Iterations | 10 |
| Network Alpha | 32 | Repeat & Steps | 25 & 1.7K+ |
| Epoch | 20 | Save Every N Epochs | 1 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 100+ [ Hi-RES ]
& More ...............
A black ford mustang parked in the parking lot, in the style of futurism influence, uhd image, furaffinity, focus, street photography, thin steel forms, 32k uhd --ar 2:3 --v 5
Ferrari car f3 458 tt, in the style of liam wong, fujifilm x-t4, multiple exposure, tsubasa nakai, uhd image, pinturicchio, crimson --ar 16:9 --v 5.2
Bugatti Veyron in cobalt blue metallic, high detail, octane render, 8k
| Parameter | Value |
|---|---|
| Prompt | Bugatti Veyron in cobalt blue metallic, high detail, octane render, 8k |
| Sampler | euler |
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 = "prithivMLmods/Canopus-Snoopy-Charlie-Brown-Flux-LoRA"
trigger_word = "Snoopy Charlie Brown" # Leave trigger_word blank if not used.
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
You should use Snoopy Charlie Brown to trigger the image generation.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.
prithivMLmods/Canopus-Snoopy-Charlie-Brown-Flux-LoRA
Image Processing Parameters
| Parameter | Value | Parameter | Value |
|---|---|---|---|
| LR Scheduler | constant | Noise Offset | 0.03 |
| Optimizer | AdamW8bit | Multires Noise Discount | 0.1 |
| Network Dim | 64 | Multires Noise Iterations | 10 |
| Network Alpha | 32 | Repeat & Steps | 25 & 1.7K+ |
| Epoch | 20 | Save Every N Epochs | 1 |
Labeling: florence2-en(natural language & English)
Total Images Used for Training : 100+ [ Hi-RES ]
& More ...............
A black ford mustang parked in the parking lot, in the style of futurism influence, uhd image, furaffinity, focus, street photography, thin steel forms, 32k uhd --ar 2:3 --v 5
Ferrari car f3 458 tt, in the style of liam wong, fujifilm x-t4, multiple exposure, tsubasa nakai, uhd image, pinturicchio, crimson --ar 16:9 --v 5.2
Bugatti Veyron in cobalt blue metallic, high detail, octane render, 8k
| Parameter | Value |
|---|---|
| Prompt | Bugatti Veyron in cobalt blue metallic, high detail, octane render, 8k |
| Sampler | euler |
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 = "prithivMLmods/Canopus-Snoopy-Charlie-Brown-Flux-LoRA"
trigger_word = "Snoopy Charlie Brown" # Leave trigger_word blank if not used.
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
You should use Snoopy Charlie Brown to trigger the image generation.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.