metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: >-
Front view, capture a urban style, Gta Hoodie, technical materials, fabric
small point label on text Green theory, the design is minimal, with a
raised collar, fabric is a Rose, low angle to capture the Hoodies form and
detailing, f/5.6 to focus on the hoodies craftsmanship, solid grey
background, studio light setting, with batman logo in the chest region of
the t-shirt
output:
url: images/YYY.png
- text: >-
Front view, capture a urban style, Hoodie, technical materials, fabric
small point label on text Graytheory, the design is minimal, with a raised
collar, fabric is a dark grey, low angle to capture the Hoodies form and
detailing, f/5.6 to focus on the hoodies craftsmanship, solid grey
background, studio light setting
output:
url: images/XXX.png
- text: >-
Front view, capture a urban style, Hoodie, technical materials, fabric
small point label on text red theory, the design is minimal, with a raised
collar, fabric is a light red, low angle to capture the Hoodies form and
detailing, f/5.6 to focus on the hoodies craftsmanship, solid grey
background, studio light setting
output:
url: images/RRR.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: Dress, Cloth, Cloth style, Material Style, Hoodie
license: creativeml-openrail-m
Canopus-Flux-LoRA-Hoodies
The model is still in the training phase. This is not the final version and may contain artifacts and perform poorly in some cases.
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 = "prithivMLmods/Canopus-Flux-LoRA-Hoodies"
trigger_word = "Cloth style" # Leave trigger_word blank if not used.
pipe.load_lora_weights(lora_repo)
device = torch.device("cuda")
pipe.to(device)
app.py
import gradio as gr
gr.load("prithivMLmods/Canopus-Flux-LoRA-Hoodies").launch()
pythonproject.py
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
import gradio as gr
def image_generator(prompt):
pass
interface = gr.Interface(fn=image_generator, inputs="text", outputs="image")
app = FastAPI()
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
app = gr.mount_gradio_app(app, interface, path="/")
Trigger words
You should use Dress
to trigger the image generation.
You should use Cloth
to trigger the image generation.
You should use Cloth style
to trigger the image generation.
You should use Material Style
to trigger the image generation.
You should use Hoodie
to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.