The main validation prompt used during training was:
woman smiling and holding two glasses of beer, She is dressed in traditional Bavarian or Alpine attire, which consists of a white lace blouse under a dark green dirndl dress. The dress is cinched at the waist with a belt that has an ornate metal clasp.
Validation settings
CFG:
3.5
CFG Rescale:
0.0
Steps:
15
Sampler:
None
Seed:
42
Resolution:
1024
Note: The validation settings are not necessarily the same as the
training settings
.
You can find some example images in the following gallery:
Prompt
unconditional (blank prompt)
Negative Prompt
'
Prompt
woman smiling and holding two glasses of beer, She is dressed in traditional Bavarian or Alpine attire, which consists of a white lace blouse under a dark green dirndl dress. The dress is cinched at the waist with a belt that has an ornate metal clasp.
Negative Prompt
'
The text encoder
was not
trained.
You may reuse the base model text encoder for inference.
Training settings
Training epochs: 199
Training steps: 200
Learning rate: 0.0001
Effective batch size: 4
Micro-batch size: 4
Gradient accumulation steps: 1
Number of GPUs: 1
Prediction type: flow-matching
Rescaled betas zero SNR: False
Optimizer: AdamW, stochastic bf16
Precision: Pure BF16
Quantised: No
Xformers: Not used
LoRA Rank: 32
LoRA Alpha: None
LoRA Dropout: 0.1
LoRA initialisation style: default
Datasets
dirndlletz7
Repeats: 0
Total number of images: 4
Total number of aspect buckets: 1
Resolution: 1.0 megapixels
Cropped: True
Crop style: center
Crop aspect: square
Inference
import torch
from diffusers import DiffusionPipeline
model_id = 'black-forest-labs/FLUX.1-dev'
adapter_id = 'histin116/dirndlletz7'
pipeline = DiffusionPipeline.from_pretrained(model_id)
pipeline.load_lora_weights(adapter_id)
prompt = "woman smiling and holding two glasses of beer, She is dressed in traditional Bavarian or Alpine attire, which consists of a white lace blouse under a dark green dirndl dress. The dress is cinched at the waist with a belt that has an ornate metal clasp."
pipeline.to('cuda'if torch.cuda.is_available() else'mps'if torch.backends.mps.is_available() else'cpu')
image = pipeline(
prompt=prompt,
num_inference_steps=15,
generator=torch.Generator(device='cuda'if torch.cuda.is_available() else'mps'if torch.backends.mps.is_available() else'cpu').manual_seed(1641421826),
width=1024,
height=1024,
guidance_scale=3.5,
).images[0]
image.save("output.png", format="PNG")
Runs of histin116 dirndlletz7 on huggingface.co
0
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
0
30-day runs
More Information About dirndlletz7 huggingface.co Model
dirndlletz7 huggingface.co is an AI model on huggingface.co that provides dirndlletz7's model effect (), which can be used instantly with this histin116 dirndlletz7 model. huggingface.co supports a free trial of the dirndlletz7 model, and also provides paid use of the dirndlletz7. Support call dirndlletz7 model through api, including Node.js, Python, http.
dirndlletz7 huggingface.co is an online trial and call api platform, which integrates dirndlletz7's modeling effects, including api services, and provides a free online trial of dirndlletz7, you can try dirndlletz7 online for free by clicking the link below.
histin116 dirndlletz7 online free url in huggingface.co:
dirndlletz7 is an open source model from GitHub that offers a free installation service, and any user can find dirndlletz7 on GitHub to install. At the same time, huggingface.co provides the effect of dirndlletz7 install, users can directly use dirndlletz7 installed effect in huggingface.co for debugging and trial. It also supports api for free installation.