Instructions to use Vijish/vijishtest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Vijish/vijishtest 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("Vijish/vijishtest") prompt = "A man in a bustling cafe vijish1234" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
vijishtest
Model trained with AI Toolkit by Ostris

- Prompt
- A man in a bustling cafe vijish1234

- Prompt
- A man in a park vijish1234

- Prompt
- A portrait of a man vijish1234
Trigger words
You should use vijish1234 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('Vijish/vijishtest', weight_name='flux_train_replicate.safetensors')
image = pipeline('a photo of pushpa').images[0]
image.save("my_image.png")
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
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Model tree for Vijish/vijishtest
Base model
black-forest-labs/FLUX.1-dev