metadata
tags:
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
- ai-toolkit
widget:
- text: >-
a person in a bustling cafe, l3omar, neatly styled hair, well-groomed
appearance, casual fashion, ambient lighting, natural vibe
output:
url: samples/1744792157246__000002000_0.jpg
- text: ' l3omar, a professional man in a corporate headshot, wearing a dark blazer and white shirt, neutral background, soft studio lighting, realistic style, sharp focus.'
output:
url: samples/1744792173968__000002000_1.jpg
- text: >-
l3omar, an asian man with neatly styled hair, playing an acoustic guitar
in a bustling cafe, relaxed expression, casual clothes, warm ambient
light, documentary style
output:
url: samples/1744792190651__000002000_2.jpg
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: l3omar
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
leomarv2-lora
Model trained with AI Toolkit by Ostris
- Prompt
- a person in a bustling cafe, l3omar, neatly styled hair, well-groomed appearance, casual fashion, ambient lighting, natural vibe
- Prompt
- l3omar, a professional man in a corporate headshot, wearing a dark blazer and white shirt, neutral background, soft studio lighting, realistic style, sharp focus.
- Prompt
- l3omar, an asian man with neatly styled hair, playing an acoustic guitar in a bustling cafe, relaxed expression, casual clothes, warm ambient light, documentary style
Trigger words
You should use l3omar to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, etc.
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.bfloat16).to('cuda')
pipeline.load_lora_weights('lccontillo/leomarv2-lora', weight_name='leomarv2-lora.safetensors')
image = pipeline('a person in a bustling cafe, l3omar, neatly styled hair, well-groomed appearance, casual fashion, ambient lighting, natural vibe').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers