lucataco / sdxl-lcm-loras

POC of SDXL-LCM LoRA combined with a Replicate LoRA for 4 second inference time

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  • 346 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 lucataco/sdxl-lcm-loras:48bdebc9 as the base model:

import replicate

training = replicate.trainings.create(
  version="lucataco/sdxl-lcm-loras:48bdebc9f383f0e9f9e321e40c1ec7f08ac7b4dd49cf777646a6498c94605051",
  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/lucataco/sdxl-lcm-loras/versions/48bdebc9f383f0e9f9e321e40c1ec7f08ac7b4dd49cf777646a6498c94605051/trainings

The API response will look like this:

{
  "id": "zz4ibbonubfz7carwiefibzgga",
  "version": "48bdebc9f383f0e9f9e321e40c1ec7f08ac7b4dd49cf777646a6498c94605051",
  "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.