Fine-tune and deploy open source models
Fine-tune and deploy Stable Diffusion, LLaMA v2, Falcon, and more – all from an easy-to-use API.
Everything you need to make models your own.
Dataset API
Programmatically upload, manage and validate datasets for tuning your models. Learn more
Fine-tuning API
Fine-tune open source models with ready-to-use training scripts. Just bring your data. Learn more
Deployment API
Deploy fine-tuned models in one click onto serverless GPUs, no infra required. Learn more
Serverless functions
Write serverless Python functions and integrate you model with any of your applications. Learn more
Fine-tune any model
Just bring your data
Stable Diffusion training config
{
"batch_size" : 4,
"learning_rate" : 1e-6,
"learning_rate_schedule" : cosine,
"warmup_percentage" : 10,
"requires_grad" : ["unet", "vae"]
}
Deploy and scale your models
import baseten import StableDiffusionPipeline
# Invoke your model
model = StableDiffusionPipeline(model_id="rwnod2q")
image url = model("a photo of sks dog playing in the snow")
image.save("dog-snow.png")
Ship your models
Building with Blueprint
I fine-tuned FLAN-T5. Can it cook?
I used Blueprint to train FLAN-T5 to generate a recipe for any dish I could dream up.
Build an avatar generator
In less than 200 lines of code you'll build a simple version of an avatar generation app like Lensa using Blueprint.
Fine-tuning with Dreambooth in Figma
See how to build a FigJam plugin to fine-tune and invoke Stable Diffusion with Dreambooth directly from Figma.
Ready to get started?
Start your project with 4 hours of free fine-tuning and model serving GPU credits.