Instructions to use Miayan/project with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Miayan/project with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Miayan/project", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
File size: 2,146 Bytes
eeb35c5 e7a2a27 eeb35c5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 | experiment:
project_name: relighting_indoors
output_dir: train_ex6_13
logging_dir: logs
report_to: tensorboard
model:
pretrained_model_name_or_path: /mnt/HDD3/miayan/paper/envs/huggingface_cache/models--stabilityai--stable-diffusion-2-1/snapshots/5cae40e6a2745ae2b01ad92ae5043f95f23644d6
revision: null
variant: null
tokenizer_name: null
hf_repo_id: Miayan/project
hf_version: null
pretrain_unet_path: scribblelight_controlnet/checkpoint-10000
resume_from_checkpoint: latest
light_encoder:
cross_dim: 768
K: 4
Bi: 4
Bc: 4
albedo_estimator:
enabled: false
version: v2
load_stage: 3
frozen_components:
- ord_model
- iid_model
- col_model
trainable_components:
- alb_model
data:
dataset_cache_dir: /mnt/HDD3/miayan/paper/relighting_datasets/
data_hf_repo_id: Miayan/physical-relighting-dataset
data_split: test
resolution: 256
dataloader_num_workers: 0
condition_mode: lightmap_normal
relighting_impl: gemini
colors:
- - 255
- 255
- 255
- - 255
- 0
- 0
- - 0
- 255
- 0
- - 0
- 0
- 255
- - 255
- 255
- 0
- - 255
- 165
- 0
- - 128
- 0
- 128
- - 255
- 192
- 203
- - 0
- 255
- 255
- - 255
- 0
- 255
intensities:
- 0.0
- 0.1
- 0.2
- 0.4
- 0.7
- 1.0
training:
batch_size: 1
num_epochs: 20
max_train_steps: null
max_train_samples: null
seed: 42
mixed_precision: 'no'
allow_tf32: true
gradient_accumulation_steps: 1
checkpointing_steps: 5000
checkpoints_total_limit: null
learning_rate: 5.0e-06
scale_lr: false
lr_scheduler: constant
lr_warmup_steps: 500
adam_beta1: 0.9
adam_beta2: 0.999
adam_weight_decay: 0.01
adam_epsilon: 1.0e-08
max_grad_norm: 1.0
use_8bit_adam: false
set_grads_to_none: false
losses:
phys_loss:
enabled: true
weight: 1.0
latent_loss:
enabled: true
weight: 1.0
image_loss:
enabled: true
weight: 1.0
area_loss:
enabled: false
weight: 10.0
intensity_loss:
enabled: false
weight: 1.0
recon_loss:
enabled: true
weight: 1.0
keep_aux_models_on_gpu: true
|