Create README.md

README.md

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+---
+license: creativeml-openrail-m
+tags:
+  - flux
+  - lora
+  - kontext
+  - avatar
+  - image-to-image
+  - style-transfer
+  - na'vi
+  - stable-diffusion
+  - art
+  - character-design
+  - ai-generated
+inference: true
+---
+
+# FLUX.1-Kontext-Dev Na'vi Style LoRA 🎨🧞‍♂️
+
+This is a LoRA adapter trained on top of the [`black-forest-labs/FLUX.1-Kontext-dev`](https://huggingface.co/black-forest-labs/FLUX.1-Kontext-dev) model to transform images into *Avatar-style Na'vi characters*, inspired by the visuals from James Cameron's *Avatar* films.
+
+## 📸 Example Outputs
+
+| Input Image | Stylized Output |
+|-------------|-----------------|
+| ![input](./examples/input.jpg) | ![output](./examples/output.jpg) |
+
+> *(Add your own examples by placing them in an `examples/` folder in the repo)*
+
+---
+
+## 🧠 Model Details
+
+- **Base Model**: FLUX.1-Kontext-dev (custom diffusion)
+- **LoRA Rank**: 4 / 8 (depending on your version)
+- **Training Resolution**: 512x512
+- **Target Style**: Na'vi characters (blue skin, elongated facial features, glowing eyes, etc.)
+- **Architecture**: LoRA fine-tuning with Stable Diffusion compatible UNet blocks.
+
+---
+
+## 💻 Usage
+
+### In Diffusers
+
+```python
+from diffusers import StableDiffusionPipeline
+from peft import PeftModel
+import torch
+
+# Load the base model
+pipe = StableDiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-Kontext-dev", torch_dtype=torch.float16).to("cuda")
+
+# Load the LoRA adapter
+pipe.unet.load_attn_procs("your-username/flux-kontext-na-vi-lora")
+
+# Use the model
+prompt = "A close-up portrait of a Na'vi warrior in a glowing forest, cinematic lighting"
+image = pipe(prompt).images[0]
+image.save("output.png")