SD3.5-Large DreamBooth LoRA - jiaxuan3040/tem_sd35_lora

Prompt
TEM_BF material_Ni ion_Kr energy_1MeV dose_0.200 temperature_600
Prompt
TEM_BF material_Ni ion_Kr energy_1MeV dose_0.200 temperature_600
Prompt
TEM_BF material_Ni ion_Kr energy_1MeV dose_0.200 temperature_600
Prompt
TEM_BF material_Ni ion_Kr energy_1MeV dose_0.200 temperature_600

Model description

These are jiaxuan3040/tem_sd35_lora DreamBooth LoRA weights for stabilityai/stable-diffusion-3.5-large.

The weights were trained using DreamBooth with the SD3 diffusers trainer.

Was LoRA for the text encoder enabled? False.

Trigger words

You should use irradiated_TEM_micrograph 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(stabilityai/stable-diffusion-3.5-large, torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('jiaxuan3040/tem_sd35_lora', weight_name='pytorch_lora_weights.safetensors')
image = pipeline('TEM_BF material_Ni ion_Kr energy_1MeV dose_0.200 temperature_600').images[0]

Use it with UIs such as AUTOMATIC1111, Comfy UI, SD.Next, Invoke

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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