Instructions to use k2styles/krea-2-deep-blue-motion-blur-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use k2styles/krea-2-deep-blue-motion-blur-lora 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-Turbo", torch_dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("k2styles/krea-2-deep-blue-motion-blur-lora") prompt = "a lighthouse on a rocky cliff. deep blue motion blur style" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Archive mirror of ilkerzgi/krea-2-deep-blue-motion-blur-lora
Browse files- .gitattributes +2 -0
- README.md +110 -0
- deep-blue-motion-blur.safetensors +3 -0
- fal-dark.png +0 -0
- fal-light.png +0 -0
- images/ex_1.png +0 -0
- images/ex_2.png +3 -0
- images/ex_3.png +3 -0
- images/ex_4.png +0 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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images/ex_2.png filter=lfs diff=lfs merge=lfs -text
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images/ex_3.png filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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language:
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- en
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base_model:
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- krea/Krea-2-Turbo
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pipeline_tag: text-to-image
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library_name: diffusers
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license: other
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license_name: krea-2-community-license
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license_link: https://huggingface.co/krea/Krea-2-LoRA-impressionist/blob/main/LICENSE.pdf
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instance_prompt: deep blue motion blur style
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tags:
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- lora
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- text-to-image
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- krea
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- krea-2
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- fal-ai
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- template:diffusion-lora
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- photographic
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widget:
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- text: "a lighthouse on a rocky cliff. deep blue motion blur style"
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output:
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url: images/ex_1.png
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- text: "a lighthouse on a rocky cliff. deep blue motion blur style"
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output:
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url: images/ex_2.png
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- text: "a lighthouse on a rocky cliff. deep blue motion blur style"
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output:
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url: images/ex_3.png
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- text: "a lighthouse on a rocky cliff. deep blue motion blur style"
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output:
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url: images/ex_4.png
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---
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<picture>
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<source media="(prefers-color-scheme: dark)" srcset="https://huggingface.co/ilkerzgi/krea-2-deep-blue-motion-blur-lora/resolve/main/fal-dark.png">
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<img src="https://huggingface.co/ilkerzgi/krea-2-deep-blue-motion-blur-lora/resolve/main/fal-light.png" alt="fal" height="18">
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</picture>
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# Deep Blue Motion Blur
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**fal · Krea 2 Style LoRA series.** One of 1600+ style LoRAs trained on [fal](https://fal.ai).
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A **Krea 2** style LoRA. Add the trigger **`deep blue motion blur style`** to the end of your prompt.
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[](https://fal.ai/models/fal-ai/krea-2/turbo/lora) [](https://fal.ai/models/fal-ai/krea-2-trainer) [](https://huggingface.co/krea/Krea-2-Turbo)
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<Gallery />
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## Quick start
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| Parameter | Value |
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|-----------|-------|
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| Trigger | `deep blue motion blur style` |
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| Recommended LoRA scale | `1.0` to `1.25` |
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| Base model | `krea/Krea-2-Turbo` |
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| Trained on | [fal-ai/krea-2-trainer](https://fal.ai/models/fal-ai/krea-2-trainer) |
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## Inference on fal
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### Python
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```python
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import fal_client
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result = fal_client.subscribe(
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"fal-ai/krea-2/turbo/lora",
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arguments={
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"prompt": "a lighthouse on a rocky cliff. deep blue motion blur style",
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"loras": [{"path": "https://huggingface.co/ilkerzgi/krea-2-deep-blue-motion-blur-lora/resolve/main/deep-blue-motion-blur.safetensors", "scale": 1.0}],
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"image_size": {"width": 1024, "height": 1280},
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},
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)
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print(result["images"][0]["url"])
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```
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### JavaScript
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```js
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import { fal } from "@fal-ai/client";
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const { data } = await fal.subscribe("fal-ai/krea-2/turbo/lora", {
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input: {
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prompt: "a lighthouse on a rocky cliff. deep blue motion blur style",
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loras: [{ path: "https://huggingface.co/ilkerzgi/krea-2-deep-blue-motion-blur-lora/resolve/main/deep-blue-motion-blur.safetensors", scale: 1.0 }],
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image_size: { width: 1024, height: 1280 },
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},
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});
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console.log(data.images[0].url);
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```
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## Train your own on fal
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Every LoRA in this series is trained on [`fal-ai/krea-2-trainer`](https://fal.ai/models/fal-ai/krea-2-trainer) (100 steps, learning rate 3.5e-4). Train your own style from 4 to 10 reference images:
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```python
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import fal_client
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result = fal_client.subscribe(
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"fal-ai/krea-2-trainer",
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arguments={
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"images_data_url": "https://.../your-dataset.zip",
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"trigger_phrase": "deep blue motion blur style",
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"steps": 100,
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"learning_rate": 0.00035,
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},
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)
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print(result)
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```
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## License
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Krea 2 Community License. See the [license](https://huggingface.co/krea/Krea-2-LoRA-impressionist/blob/main/LICENSE.pdf).
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deep-blue-motion-blur.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:8110aa97a65d5eca739aa290131397153b3f4faa42c05d674b3c8c72aede5e26
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size 234677320
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fal-dark.png
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fal-light.png
ADDED
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images/ex_1.png
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images/ex_2.png
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Git LFS Details
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images/ex_3.png
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Git LFS Details
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images/ex_4.png
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