---
license: openrail++
language:
- en
library_name: diffusers
pipeline_tag: text-to-image
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: k0d4chr0me
tags:
- lora
- stable-diffusion-xl
- text-to-image
- diffusers
- style
- vintage
- film
- kodachrome
- 1970s
- analog
- photography
- retro
- flux
- cinematic
- flux lora
- style-lora
- portrait
- landscape
- illustration
widget:
  - text: "k0d4chr0me, professional portrait of an elderly fisherman, weathered face, soft natural lighting"
  - text: "k0d4chr0me, golden retriever on a wooden porch, autumn light"
  - text: "k0d4chr0me, vintage motorcycle on a coastal road, sunset"
---

# Kodachrome 1970s Vintage Film Look with Flux LoRA

## What it does
Immerse yourself in the nostalgic charm of Kodachrome 64 film from the 1970s with this LoRA model, delivering a unique aesthetic characterized by its warm and saturated colors, distinctive red-orange shadow shifts, subtle grain texture, and signature 'Kodachrome glow' in highlights.
## How to use
Apply the trigger word 'k0d4chr0me' in your prompts for seamless integration. Ideal strength ranges from 0.85 to 1.0, paired with FluxGuidance settings of 3.0-4.0 for optimal results.
## Best for
- Professional portraits with a vintage feel
- Capturing the essence of pets and landscapes under autumn light
- Coastal road scenes during sunsets
- Morning coffee moments on windowsills
- Jazz musicians performing in atmospheric bars
## Tips
- Enhance your images by adjusting lighting to complement the film's warmth.
- Combine this LoRA with other complementary models for a multi-layered effect.

## Trigger word

Activate with `k0d4chr0me`. Recommended strength: **0.9**.

## Showcase

![showcase 1](./showcase/showcase_01.png)
![showcase 2](./showcase/showcase_02.png)
![showcase 3](./showcase/showcase_03.png)
![showcase 4](./showcase/showcase_04.png)
![showcase 5](./showcase/showcase_05.png)
![showcase 6](./showcase/showcase_06.png)
![showcase 7](./showcase/showcase_07.png)
![showcase 8](./showcase/showcase_08.png)

## Usage with `diffusers`

```python
from diffusers import AutoPipelineForText2Image
import torch

pipe = AutoPipelineForText2Image.from_pretrained("black-forest-labs/FLUX.1-dev", torch_dtype=torch.float16).to("cuda")
pipe.load_lora_weights("strkyyy/kodachrome-1970s")
image = pipe("k0d4chr0me, your prompt", num_inference_steps=30).images[0]
```