Text-to-Image
Diffusers
Safetensors
FluxPipeline
diffusers-training
flux
flux-diffusers
template:sd-lora
import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("balajivai/dreambooth-model", dtype=torch.bfloat16, device_map="cuda")
prompt = "abab glass bottle"
image = pipe(prompt).images[0]Flux [dev] DreamBooth - balajivai/dreambooth-model
Model description
These are balajivai/dreambooth-model DreamBooth weights for black-forest-labs/FLUX.1-dev.
The weights were trained using DreamBooth with the Flux diffusers trainer.
Was the text encoder fine-tuned? False.
Trigger words
You should use abab glass bottle to trigger the image generation.
Use it with the 🧨 diffusers library
from diffusers import AutoPipelineForText2Image
import torch
pipeline = AutoPipelineForText2Image.from_pretrained('balajivai/dreambooth-model', torch_dtype=torch.bfloat16).to('cuda')
image = pipeline('abab glass bottle').images[0]
License
Please adhere to the licensing terms as described here.
Intended uses & limitations
How to use
# TODO: add an example code snippet for running this diffusion pipeline
Limitations and bias
[TODO: provide examples of latent issues and potential remediations]
Training details
[TODO: describe the data used to train the model]
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Model tree for balajivai/dreambooth-model
Base model
black-forest-labs/FLUX.1-dev