Instructions to use AlekseyCalvin/Portra800 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use AlekseyCalvin/Portra800 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("AlekseyCalvin/Portra800") prompt = "TOK style" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
| license: unlicense | |
| tags: | |
| - text-to-image | |
| - stable-diffusion | |
| - lora | |
| - diffusers | |
| - template:sd-lora | |
| - flux | |
| - flux dev | |
| - photo | |
| base_model: black-forest-labs/FLUX.1-dev | |
| instance_prompt: TOK style | |
| # Kodak Portra 800-inspired Realistic Model by Shapestudio (Fine-tuned from Flux Schnell/Dev) | |
| <Gallery /> | |
| ## Model description | |
| Also found/usable via Replicate [HERE](https://replicate.com/shapestudio/portra-800-flux) | |
| ## Trigger words | |
| You should use 'TOK style' to trigger the image generation. | |
| --- | |