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README.md
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instance_prompt: TOK
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---
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#
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<Gallery />
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## About this LoRA
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This is a [LoRA](https://replicate.com/docs/guides/working-with-loras) for the FLUX.1-dev text-to-image model. It can be used with diffusers or ComfyUI.
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It was trained on [Replicate](https://replicate.com/) using AI toolkit: https://replicate.com/ostris/flux-dev-lora-trainer/train
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## Trigger words
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You should use `TOK` to trigger the image generation.
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## Run this LoRA with an API using Replicate
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```py
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import replicate
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input = {
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"prompt": "TOK",
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"lora_weights": "https://huggingface.co/codermert/ozgeefinal/resolve/main/lora.safetensors"
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}
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output = replicate.run(
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"black-forest-labs/flux-dev-lora",
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input=input
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)
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for index, item in enumerate(output):
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with open(f"output_{index}.webp", "wb") as file:
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file.write(item.read())
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```
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## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
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from diffusers import AutoPipelineForText2Image
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import torch
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pipeline
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```
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For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
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## Training details
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- Steps: 2000
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- Learning rate: 0.0004
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- LoRA rank: 16
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## Contribute your own examples
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You can use the [community tab](https://huggingface.co/codermert/ozgeefinal/discussions) to add images that show off what you’ve made with this LoRA.
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instance_prompt: TOK
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---
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# Malika
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<Gallery />
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## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)
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from diffusers import AutoPipelineForText2Image
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import torch
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# 1. Realistic Vision modelini yükle
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pipeline = AutoPipelineForText2Image.from_pretrained(
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"prithivMLmods/Canopus-LoRA-Flux-UltraRealism-2.0",
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torch_dtype=torch.float16
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).to("cuda")
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# 2. LoRA'yı zorla yükle (alpha=0.5 ile gücünü azaltın)
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pipeline.load_lora_weights(
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"codermert/ozgeefinal",
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weight_name="lora.safetensors",
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adapter_name="fluxx",
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cross_attention_scale=0.5 # LoRA etkisini hafiflet
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)
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# 3. Promptta hem trigger hem stil vurgusu yapın
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image = pipeline(
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prompt="portrait of TOK, <fluxx>, photorealistic, 8K", # TOK + adapter_name
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negative_prompt="blurry, deformed"
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).images[0]
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```
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For more details, including weighting, merging and fusing LoRAs, check the [documentation on loading LoRAs in diffusers](https://huggingface.co/docs/diffusers/main/en/using-diffusers/loading_adapters)
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