Text-to-Image
Diffusers
Safetensors
English
Portuguese
StableDiffusionXLPipeline
stable-diffusion-xl
imageflow
Instructions to use BinaryLight1011/Imageflow with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BinaryLight1011/Imageflow with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BinaryLight1011/Imageflow", 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 Settings
- Draw Things
- DiffusionBee
| license: creativeml-openrail-m | |
| language: | |
| - en | |
| - pt | |
| tags: | |
| - text-to-image | |
| - stable-diffusion-xl | |
| - diffusers | |
| - imageflow | |
| base_model: stabilityai/stable-diffusion-xl-base-1.0 | |
| pipeline_tag: text-to-image | |
| # 🌊 Imageflow.1.1.1 | |
| **Text-to-Image** model by [jeffvedd](https://huggingface.co/jeffvedd) | |
| Base: `stabilityai/stable-diffusion-xl-base-1.0` | |
| Framework: 🤗 Diffusers | |
| ## 🚀 Uso Rápido | |
| ```python | |
| from diffusers import StableDiffusionXLPipeline | |
| import torch | |
| pipe = StableDiffusionXLPipeline.from_pretrained( | |
| 'jeffvedd/Imageflow', | |
| torch_dtype=torch.float16, | |
| use_safetensors=True, | |
| ).to('cuda') | |
| image = pipe( | |
| prompt='A futuristic city at night, neon lights, ultra detailed', | |
| negative_prompt='blurry, low quality', | |
| num_inference_steps=30, | |
| guidance_scale=7.5, | |
| ).images[0] | |
| image.save('output.png') | |
| ``` | |
| ## ⚙️ Parâmetros Recomendados | |
| | Parâmetro | Valor | | |
| |-----------|-------| | |
| | `guidance_scale` | 7.0 – 9.0 | | |
| | `num_inference_steps` | 25 – 40 | | |
| | `resolution` | 1024×1024 | | |
| **Autor:** jeffvedd · **Treinado em:** Kaggle GPU | |