Failed to load versions. Head to the versions page to see all versions for this model.
You're looking at a specific version of this model. Jump to the model overview.
vetkastar /lora-train:268538de
Input
Run this model in Node.js with one line of code:
npm install replicate
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import Replicate from "replicate";
const replicate = new Replicate({
auth: process.env.REPLICATE_API_TOKEN,
});
Run vetkastar/lora-train using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
const output = await replicate.run(
"vetkastar/lora-train:268538dec5f1f07500511dae6d896250773f7cb3f207f314bdd935fcbb191f03",
{
input: {
sdxl: true,
seed: 1,
unet_lr: 0.0001,
flip_aug: false,
xformers: true,
clip_skip: 1,
color_aug: false,
full_bf16: false,
full_fp16: false,
lr_warmup: 10,
resolution: "1024,1024",
save_state: false,
keep_tokens: 1,
network_dim: 128,
lr_scheduler: "constant_with_warmup",
learning_rate: 0.000002,
network_alpha: 128,
save_model_as: "safetensors",
network_module: "networks.lora",
optimizer_type: "AdamW8bit",
save_precision: "bf16",
dataset_repeats: 75,
max_train_steps: 9999,
mixed_precision: "bf16",
shuffle_caption: false,
text_encoder_lr: 0.00005,
lora_output_name: "Lora",
max_token_length: 150,
max_train_epochs: 1,
save_safetensors: true,
train_batch_size: 8,
bucket_no_upscale: false,
bucket_reso_steps: 32,
prior_loss_weight: 1,
scale_weight_norms: 0,
save_every_n_epochs: 1,
caption_dropout_rate: 0,
gradient_checkpointing: true,
max_data_loader_n_workers: 0,
gradient_accumulation_steps: 1,
pretrained_model_name_or_path: "files/model/juggernautXL_version6Rundiffusion.safetensors",
caption_dropout_every_n_epochs: 0,
persistent_data_loader_workers: false
}
}
);
console.log(output);
To learn more, take a look at the guide on getting started with Node.js.
pip install replicate
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
import replicate
Run vetkastar/lora-train using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
output = replicate.run(
"vetkastar/lora-train:268538dec5f1f07500511dae6d896250773f7cb3f207f314bdd935fcbb191f03",
input={
"sdxl": True,
"seed": 1,
"unet_lr": 0.0001,
"flip_aug": False,
"xformers": True,
"clip_skip": 1,
"color_aug": False,
"full_bf16": False,
"full_fp16": False,
"lr_warmup": 10,
"resolution": "1024,1024",
"save_state": False,
"keep_tokens": 1,
"network_dim": 128,
"lr_scheduler": "constant_with_warmup",
"learning_rate": 0.000002,
"network_alpha": 128,
"save_model_as": "safetensors",
"network_module": "networks.lora",
"optimizer_type": "AdamW8bit",
"save_precision": "bf16",
"dataset_repeats": 75,
"max_train_steps": 9999,
"mixed_precision": "bf16",
"shuffle_caption": False,
"text_encoder_lr": 0.00005,
"lora_output_name": "Lora",
"max_token_length": 150,
"max_train_epochs": 1,
"save_safetensors": True,
"train_batch_size": 8,
"bucket_no_upscale": False,
"bucket_reso_steps": 32,
"prior_loss_weight": 1,
"scale_weight_norms": 0,
"save_every_n_epochs": 1,
"caption_dropout_rate": 0,
"gradient_checkpointing": True,
"max_data_loader_n_workers": 0,
"gradient_accumulation_steps": 1,
"pretrained_model_name_or_path": "files/model/juggernautXL_version6Rundiffusion.safetensors",
"caption_dropout_every_n_epochs": 0,
"persistent_data_loader_workers": False
}
)
print(output)
To learn more, take a look at the guide on getting started with Python.
REPLICATE_API_TOKEN
environment variableexport REPLICATE_API_TOKEN=<paste-your-token-here>
Find your API token in your account settings.
Run vetkastar/lora-train using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.
curl -s -X POST \
-H "Authorization: Bearer $REPLICATE_API_TOKEN" \
-H "Content-Type: application/json" \
-H "Prefer: wait" \
-d $'{
"version": "268538dec5f1f07500511dae6d896250773f7cb3f207f314bdd935fcbb191f03",
"input": {
"sdxl": true,
"seed": 1,
"unet_lr": 0.0001,
"flip_aug": false,
"xformers": true,
"clip_skip": 1,
"color_aug": false,
"full_bf16": false,
"full_fp16": false,
"lr_warmup": 10,
"resolution": "1024,1024",
"save_state": false,
"keep_tokens": 1,
"network_dim": 128,
"lr_scheduler": "constant_with_warmup",
"learning_rate": 0.000002,
"network_alpha": 128,
"save_model_as": "safetensors",
"network_module": "networks.lora",
"optimizer_type": "AdamW8bit",
"save_precision": "bf16",
"dataset_repeats": 75,
"max_train_steps": 9999,
"mixed_precision": "bf16",
"shuffle_caption": false,
"text_encoder_lr": 0.00005,
"lora_output_name": "Lora",
"max_token_length": 150,
"max_train_epochs": 1,
"save_safetensors": true,
"train_batch_size": 8,
"bucket_no_upscale": false,
"bucket_reso_steps": 32,
"prior_loss_weight": 1,
"scale_weight_norms": 0,
"save_every_n_epochs": 1,
"caption_dropout_rate": 0,
"gradient_checkpointing": true,
"max_data_loader_n_workers": 0,
"gradient_accumulation_steps": 1,
"pretrained_model_name_or_path": "files/model/juggernautXL_version6Rundiffusion.safetensors",
"caption_dropout_every_n_epochs": 0,
"persistent_data_loader_workers": false
}
}' \
https://api.replicate.com/v1/predictions
To learn more, take a look at Replicate’s HTTP API reference docs.
Add a payment method to run this model.
By signing in, you agree to our
terms of service and privacy policy
Output
No output yet! Press "Submit" to start a prediction.