Stable Diffusion Dreambooth微调API

请求方法

POST

请求地址

https://api.lanrui.co/api/sd/train/dreambooth

CURL 示例

curl --location 'https://api.lanrui.co/api/sd/train/dreambooth' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer {填入API Key，删除花括号}' \
--data 'request_dict = {
    "pretrained_model_name_or_path": "runwayml/stable-diffusion-v1-5",
    "train_batch_size": 1,
    "bucket_no_upscale": true,
    "bucket_reso_steps": 1.0,
    "caption_dropout_every_n_epochs": 0.0,
    "caption_dropout_rate": 0.1,
    "clip_skip": 1,
    "color_aug": false,
    "repeats": 10,
    "epoch": 2,
    "flip_aug": false,
    "gradient_accumulation_steps": 1.0,
    "keep_tokens": 1,
    "learning_rate": "0.0000166666666",
    "lr_scheduler": "cosine",
    "lr_warmup": 10,
    "max_bucket_reso": 1024,
    "max_resolution": "512,512",
    "max_token_length": 150,
    "min_bucket_reso": 256,
    "mixed_precision": "bf16",
    "optimizer": "Lion",
    "random_crop": false,
    "save_every_n_epochs": 1,
    "save_precision": "fp16",
    "shuffle_caption": true,
    "train_batch_size": 4
}'

请求 Body 参数（application/json）

参数名	参数类型	取值范围	参数释义	是否必填
pretrained_model_name_or_path	string	默认值: `runwayml/stable-diffusion-v1-5` 取值范围: `stabilityai/stable-diffusion-xl-base-1.0` `runwayml/stable-diffusion-v1-5`	Pretrained model name	否
sdxl	boolean	默认值: `False`	sdxl	否
repeats	integer	默认值: `10`	The number of times an image is reused within an epoch	否
train_batch_size	integer	默认值: `1` 取值范围: `[1, inf)`	Batch size for training	否
epoch	integer	默认值: `20` 取值范围: `[1, inf)`	Epoch size for training	否
mixed_precision	string	默认值: `fp16` 取值范围: `no` `fp16` `bf16` `fp8`	Whether or not to use mixed precision training	否
train_data_dir	string	默认值: `空`	Image folder (containing training images subfolders)	否
max_resolution	string	默认值: `512,512`	Max resolution (width, height)	否
color_aug	boolean	默认值: `False`	Enable weak color augmentation	否
flip_aug	boolean	默认值: `False`	Enable horizontal flip augmentation	否
output_dir	string	默认值: `空`	Output directory for trained model	否
save_every_n_epochs	integer	默认值: `10` 取值范围: `[1, inf)`	Save every N epochs	否
save_precision	string	默认值: `fp16` 取值范围: `float` `fp16` `bf16`	Save precision	否
learning_rate	number	默认值: `1e-06` 取值范围: `[0.0, inf)`	Learning rate (Set to 0 to not train the Unet)	否
learning_rate_te	number	默认值: `1e-06` 取值范围: `[0.0, 1.0]`	Learning rate TE (Set to 0 to not train the Text Encoder)	否
learning_rate_te1	number	默认值: `1e-06` 取值范围: `[0.0, 1.0]`	Learning rate TE1 (Set to 0 to not train the Text Encoder 1)	否
learning_rate_te2	number	默认值: `1e-06` 取值范围: `[0.0, 1.0]`	Learning rate TE2 (Set to 0 to not train the Text Encoder 2)	否
lr_scheduler	string	默认值: `constant` 取值范围: `constant` `adafactor` `constant_with_warmup` `cosine` `cosine_with_restarts` `linear` `polynomial`	LR Scheduler	否
lr_warmup	number	默认值: `0` 取值范围: `[0.0, inf)`	LR warmup (% of total steps) Can't use LR warmup with LR Scheduler constant... setting to 0 and disabling field...	否
lr_scheduler_num_cycles	integer	默认值: `1` 取值范围: `[1, inf)`	Number of restarts for cosine scheduler with restarts	否
lr_scheduler_power	number	默认值: `1.0` 取值范围: `[0.0, inf)`	Polynomial power for polynomial scheduler	否
optimizer	string	默认值: `PagedAdamW8bit` 取值范围: `AdamW` `AdamW8bit` `Adafactor` `DAdaptation` `DAdaptAdaGrad` `DAdaptAdam` `DAdaptAdan` `DAdaptAdanIP` `DAdaptAdamPreprint` `DAdaptLion` `DAdaptSGD` `Lion` `Lion8bit` `PagedAdamW8bit` `PagedAdamW32bit` `PagedLion8bit` `Prodigy` `SGDNesterov` `SGDNesterov8bit`	Optimizer	否
min_snr_gamma	integer	默认值: `0` 取值范围: `[0, 20]`	Recommended value of 5 when used	否
shuffle_caption	boolean	默认值: `False`	Shuffle caption	否
keep_tokens	integer	默认值: `0` 取值范围: `[0, 32]`	Keep n tokens	否
no_token_padding	boolean	默认值: `False`	No token padding	否
max_token_length	integer	默认值: `75` 取值范围: `75` `150` `225`	max token length of text encoder	否
noise_offset_type	string	默认值: `Original` 取值范围: `Original` `Multires`	Noise offset type	否
noise_offset	number	默认值: `0` 取值范围: `[0.0, 1.0]`	Recommended values are 0.05 - 0.15	否
noise_offset_random_strength	boolean	默认值: `False`	Use random strength between 0~noise_offset for noise offset	否
adaptive_noise_scale	number	默认值: `0` 取值范围: `[-1.0, 1.0]`	Add `latent mean absolute value * this value` to noise_offset	否
multires_noise_iterations	integer	默认值: `0` 取值范围: `[0, 64]`	Enable multires noise (recommended values are 6-10)	否
multires_noise_discount	number	默认值: `0.3` 取值范围: `[0.0, 1.0]`	Recommended values are 0.8. For LoRAs with small datasets, 0.1-0.3	否
sample_every_n_epochs	integer	默认值: `0`	Sample every n epochs	否
sample_sampler	string	默认值: `euler_a` 取值范围: `ddim` `pndm` `lms` `euler` `euler_a` `heun` `dpm_2` `dpm_2_a` `dpmsolver` `dpmsolver++` `dpmsingle` `k_lms` `k_euler` `k_euler_a` `k_dpm_2` `k_dpm_2_a`	Sample sampler	否
sample_prompts	string	默认值: `空`	Enter one sample prompt per line to generate multiple samples per cycle. Optional specifiers include: --w (width), --h (height), --d (seed), --l (cfg scale), --s (sampler steps) and --n (negative prompt). eg: masterpiece, best quality, 1girl, in white shirts, upper body, looking at viewer, simple background --n low quality, worst quality, bad anatomy,bad composition, poor, low effort --w 768 --h 768 --d 1 --l 7.5 --s 28	否
seed	integer	默认值: `0` 取值范围: `[0, inf)`	Seed (Set to 0 to make random)	否
clip_skip	integer	默认值: `1` 取值范围: `[0, 12]`	Clip skip	否
stop_text_encoder_training	integer	默认值: `0` 取值范围: `[-1, 100]`	Stop TE (% of total steps)	否
gradient_accumulation_steps	integer	默认值: `1` 取值范围: `[1, 120]`	Number of updates steps to accumulate before performing a backward/update pass	否
optimizer_args	string	默认值: `空`	(Optional) eg: relative_step=True scale_parameter=True warmup_init=True	否
lr_scheduler_args	string	默认值: `空`	(Optional) eg: milestones=[1,10,30,50] gamma=0.1	否
enable_bucket	boolean	默认值: `True`	Enable buckets	否
random_crop	boolean	默认值: `False`	Random crop instead of center crop	否
min_bucket_reso	integer	默认值: `64` 取值范围: `[64, 4096]`	Minimum size in pixel a bucket can be (>= 64)	否
max_bucket_reso	integer	默认值: `2048` 取值范围: `[64, 4096]`	Maximum size in pixel a bucket can be (>= 64)	否
bucket_no_upscale	boolean	默认值: `True`	Don't upscale bucket resolution	否
bucket_reso_steps	integer	默认值: `64` 取值范围: `[1, 128]`	Bucket resolution steps	否
caption_dropout_every_n_epochs	integer	默认值: `0`	Dropout caption every n epochs	否
caption_dropout_rate	number	默认值: `0` 取值范围: `[0.0, 1.0]`	Rate of caption dropout	否
weighted_captions	boolean	默认值: `False`	Enable weighted captions in the standard style (token:1.3). No commas inside parens, or shuffle/dropout may break the decoder.	否
ip_noise_gamma	number	默认值: `0` 取值范围: `[0.0, 1.0]`	Enable input perturbation noise. used for regularization. recommended value: around 0.1	否
ip_noise_gamma_random_strength	boolean	默认值: `False`	Use random strength between 0~ip_noise_gamma for input perturbation noise	否
min_timestep	integer	默认值: `0` 取值范围: `[0, 1000]`	Values greater than 0 will make the model more img2img focussed. 0 = image only	否
max_timestep	integer	默认值: `1000` 取值范围: `[0, 1000]`	Values lower than 1000 will make the model more img2img focussed. 1000 = noise only	否

请求方法​

请求地址​

请求 Body 参数（application/json）​

返回响应（json）​

请求方法

请求地址

请求 Body 参数（application/json）

返回响应（json）