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("meoconxinhxan/emad_test")
prompt = "<EMAD> running the inc that open source code, models and datasets powering & powered by AI money"
image = pipe(prompt).images[0]Flux DreamBooth LoRA - tuenguyen/emad_test
- Prompt
- <EMAD> running the inc that open source code, models and datasets powering & powered by AI money
- Prompt
- <EMAD> running the inc that open source code, models and datasets powering & powered by AI money
- Prompt
- <EMAD> running the inc that open source code, models and datasets powering & powered by AI money
- Prompt
- <EMAD> running the inc that open source code, models and datasets powering & powered by AI money
Model description
These are tuenguyen/emad_test DreamBooth LoRA weights for black-forest-labs/FLUX.1-dev.
The weights were trained using DreamBooth with the Flux diffusers trainer.
Was LoRA for the text encoder enabled? False.
Trigger words
You should use <EMAD> to trigger the image generation.
Download model
Download the *.safetensors LoRA 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('tuenguyen/emad_test', weight_name='pytorch_lora_weights.safetensors')
image = pipeline('<EMAD> running the inc that open source code, models and datasets powering & powered by AI money').images[0]
For more details, including weighting, merging and fusing LoRAs, check the documentation on loading LoRAs in diffusers
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 meoconxinhxan/emad_test
Base model
black-forest-labs/FLUX.1-dev