Instructions to use Wahlanmol/wahl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Wahlanmol/wahl with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Wahlanmol/wahl") prompt = "create a image of wahl as a very handsome guy and image till belt area without broading up the camara and away from face, in grey shirt simling at camara ver decently, witha black studio background and image full image exluding legs only" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Wahl

- Prompt
- create a image of wahl as a very handsome guy and image till belt area without broading up the camara and away from face, in grey shirt simling at camara ver decently, witha black studio background and image full image exluding legs only
Trained on Replicate using:
https://replicate.com/ostris/flux-dev-lora-trainer/train
Trigger words
You should use wahl to trigger the image generation.
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.float16).to('cuda')
pipeline.load_lora_weights('Wahlanmol/wahl', weight_name='lora.safetensors')
image = pipeline('your prompt').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
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Model tree for Wahlanmol/wahl
Base model
black-forest-labs/FLUX.1-dev