![](https://github.com/batouresearch.png)
batouresearch
/
sdxl-lcm-lora-controlnet
An extremely fast all-in-one model to use LCM with SDXL, ControlNet and custom LoRA url's!
- Public
- 12K runs
- GitHub
If you haven’t yet trained a model on Replicate, we recommend you read one of the following guides.
Pricing
Trainings for this model run on Nvidia A100 (80GB) GPU hardware, which costs $0.0014 per second.
Create a training
Install the Python library:
pip install replicate
Then, run this to create a training with batouresearch/sdxl-lcm-lora-controlnet:d9db096a as the base model:
import replicate
training = replicate.trainings.create(
version="batouresearch/sdxl-lcm-lora-controlnet:d9db096aec79855d1f42d2bd4fc89f2b1ddf7dcd00118a0e21b8f1d5c03be099",
input={
...
},
destination=f"{username}/<destination-model-name>"
)
print(training)
curl -s -X POST \
-d '{"destination": "{username}/<destination-model-name>", "input": {...}}' \
-H "Authorization: Bearer $REPLICATE_API_TOKEN" \
https://api.replicate.com/v1/models/batouresearch/sdxl-lcm-lora-controlnet/versions/d9db096aec79855d1f42d2bd4fc89f2b1ddf7dcd00118a0e21b8f1d5c03be099/trainings
The API response will look like this:
{
"id": "zz4ibbonubfz7carwiefibzgga",
"version": "d9db096aec79855d1f42d2bd4fc89f2b1ddf7dcd00118a0e21b8f1d5c03be099",
"status": "starting",
"input": {
"data": "..."
},
"output": null,
"error": null,
"logs": null,
"started_at": null,
"created_at": "2023-03-28T21:47:58.566434Z",
"completed_at": null
}
Note that before you can create a training, you’ll need to create a model and use its name as the value for the destination field.