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fermatresearch
/
dpo-sdxl-controlnet-lora
DPO-SDXL Canny controlnet with LoRA support.
- Public
- 682 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 L40S GPU hardware, which costs $0.000975 per second.
Create a training
Install the Python library:
pip install replicate
Then, run this to create a training with fermatresearch/dpo-sdxl-controlnet-lora:5779933f as the base model:
import replicate
training = replicate.trainings.create(
version="fermatresearch/dpo-sdxl-controlnet-lora:5779933f36e3ecc23c51c18de01caff6aa54ea9e147ef3edf0b2924191595216",
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/fermatresearch/dpo-sdxl-controlnet-lora/versions/5779933f36e3ecc23c51c18de01caff6aa54ea9e147ef3edf0b2924191595216/trainings
The API response will look like this:
{
"id": "zz4ibbonubfz7carwiefibzgga",
"version": "5779933f36e3ecc23c51c18de01caff6aa54ea9e147ef3edf0b2924191595216",
"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.