Hatano Yui Lora Flux NF4

- Prompt
- Training With QLoRA: The image features Hatano Yui, wearing a red dress with gold detailing, holding a microphone. She's smiling and waving her hand directly at the camera, suggesting she's speaking at an event. Behind her, a partially obscured black and white photo serves as a backdrop. The overall impression is that Hatano Yui is presenting or speaking at event, potentially a gaming convention or awards show.

- Prompt
- Training Without QLoRA: The image features Hatano Yui, wearing a red dress with gold detailing, holding a microphone. She's smiling and waving her hand directly at the camera, suggesting she's speaking at an event. Behind her, a partially obscured black and white photo serves as a backdrop. The overall impression is that Hatano Yui is presenting or speaking at event, potentially a gaming convention or awards show.

- Prompt
- Testing With QLoRA: Ultra high Definition full body picture of Hatano Yui in leather jacket sitting on a red racing motorbike, She Sits bent over and snuggles with her upper body against the large tank of the motorcycle. her expression is self-confident and calm. Side view, outdoor setting on a pacific highway.

- Prompt
- Testing Without QLoRA: Ultra high Definition full body picture of Hatano Yui in leather jacket sitting on a red racing motorbike, She Sits bent over and snuggles with her upper body against the large tank of the motorcycle. her expression is self-confident and calm. Side view, outdoor setting on a pacific highway.
波多野結衣 / はたのゆい / Hatano Yui
All files are also archived in https://github.com/je-suis-tm/huggingface-archive in case this gets censored.
The QLoRA fine-tuning process of hatano_yui_lora_flux_nf4 takes inspiration from this post (https://huggingface.co/blog/flux-qlora). The training was executed on a local computer with 1200 timesteps and the same parameters as the link mentioned above, which took around 8 hours on 8GB VRAM 4060. The peak VRAM usage was around 7.7GB. To avoid running low on VRAM, both transformers and text_encoder were quantized. The biggest challenge of training Japanese actresses is their photos used heavy filters to whiten and smoothen the skin. This practise severely distorts the training images which makes the result less convincing than Hollywood actresses. This training dataset contains a lot of face closeup which makes result more aligned with her actual face. The tradeoff is the overfitting problem of QLoRA which makes model more likely to ignore the prompt. All the images generated here are using the below parameters
- Height: 512
- Width: 512
- Guidance scale: 5
- Num inference steps: 20
- Max sequence length: 512
- Seed: 0
Usage
import torch
from diffusers import FluxPipeline, FluxTransformer2DModel
from transformers import T5EncoderModel
text_encoder_4bit = T5EncoderModel.from_pretrained(
"hf-internal-testing/flux.1-dev-nf4-pkg", subfolder="text_encoder_2",torch_dtype=torch.float16,)
transformer_4bit = FluxTransformer2DModel.from_pretrained(
"hf-internal-testing/flux.1-dev-nf4-pkg", subfolder="transformer",torch_dtype=torch.float16,)
pipe = FluxPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.float16,
transformer=transformer_4bit,text_encoder_2=text_encoder_4bit)
pipe.load_lora_weights("je-suis-tm/hatano_yui_lora_flux_nf4",
weight_name='pytorch_lora_weights.safetensors')
prompt="Ultra high Definition full body picture of Hatano Yui in leather jacket sitting on a red racing motorbike, She Sits bent over and snuggles with her upper body against the large tank of the motorcycle. her expression is self-confident and calm. Side view, outdoor setting on a pacific highway."
image = pipe(
prompt,
height=512,
width=512,
guidance_scale=5,
num_inference_steps=20,
max_sequence_length=512,
generator=torch.Generator("cpu").manual_seed(0),
).images[0]
image.save("hatano_yui_lora_flux_nf4.png")
Trigger words
You should use Hatano Yui to trigger the image generation.
Download model
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Base model
black-forest-labs/FLUX.1-dev