Instructions to use TensorStack/StableDiffusionXL-ts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use TensorStack/StableDiffusionXL-ts with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("TensorStack/StableDiffusionXL-ts", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
File size: 1,155 Bytes
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pipeline_tag: text-to-image
---
# StableDiffusionXL-ts
Original model: https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0
Model repository for `TensorStack` library and the windows `Diffuse` application
## C# Inference Demo
```csharp
// Pipeline Config
var pipelineConfig = new PipelineConfig
{
Path = "TensorStack/StableDiffusionXL-ts",
Pipeline = "StableDiffusionXLPipeline",
ProcessType = ProcessType.TextToImage,
DataType = DataType.Bfloat16
};
// Create Pipeline
using (var pythonPipeline = new PythonPipeline(pipelineConfig, PipelineProgress.ConsoleCallback))
{
// Download/Load Model
await pythonPipeline.LoadAsync();
// Generate Option
var options = new PipelineOptions
{
Prompt = "Cute doggo riding a bicycle",
Steps = 30,
Width = 1024,
Height = 1024,
GuidanceScale = 7f,
Scheduler = SchedulerType.DDPM
};
// Generate
var response = await pythonPipeline.GenerateAsync(options);
// Save Image
await response
.AsImageTensor()
.SaveAsync("Result.png");
}
```
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