Instructions to use September6969/raven with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use September6969/raven with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("krea/Krea-2-Raw", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("September6969/raven") prompt = "A close-up portrait photo of vzx woman, looking directly at the camera, natural daylight, realistic photography" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Krea 2 LoRA โ September6969/raven

- Prompt
- A close-up portrait photo of vzx woman, looking directly at the camera, natural daylight, realistic photography

- Prompt
- A full-body photo of vzx woman standing on a city street, wearing a white T-shirt and blue jeans, natural daylight, realistic photography

- Prompt
- A cinematic portrait of vzx woman sitting in a modern cafe, wearing a black jacket, warm indoor lighting, realistic photography
A DreamBooth-LoRA for Krea 2, trained on Krea 2 RAW and shown on Krea 2 Turbo. The samples below were generated with this LoRA on Turbo (8 steps).
Trigger
Use the token vzx woman to invoke the concept.
Samples
"A close-up portrait photo of vzx woman, looking directly at the camera, natural daylight, realistic photography"
"A full-body photo of vzx woman standing on a city street, wearing a white T-shirt and blue jeans, natural daylight, realistic photography"
"A cinematic portrait of vzx woman sitting in a modern cafe, wearing a black jacket, warm indoor lighting, realistic photography"
Use it with diffusers
import torch
from diffusers import Krea2Pipeline
pipe = Krea2Pipeline.from_pretrained("krea/Krea-2-Turbo", torch_dtype=torch.bfloat16).to("cuda")
pipe.load_lora_weights("September6969/raven")
image = pipe("A close-up portrait photo of vzx woman, looking directly at the camera, natural daylight, realistic photography", num_inference_steps=8, guidance_scale=0.0).images[0]
image.save("output.png")
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Model tree for September6969/raven
Base model
krea/Krea-2-Raw

