codecandy/super-realism

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Model description for super realism engine

Image Processing Parameters

Comparison between the base model and related models.

Comparison between the base model FLUX.1-dev and its adapter, a LoRA model tuned for super-realistic realism. [ 28 steps ]

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However, it performs better in various aspects compared to its previous models, including face realism, ultra-realism, and others. previous versions [ 28 steps ]

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Previous Model Links

Hosted/Demo Links

Model Training Basic Details

Flux-Super-Realism-LoRA Model GitHub

API Usage / Quick Usage

from gradio_client import Client

client = Client("prithivMLmods/FLUX-REALISM")
result = client.predict(
		prompt="A tiny astronaut hatching from an egg on the moon, 4k, planet theme",
		seed=0,
		width=1024,
		height=1024,
		guidance_scale=6,
		randomize_seed=True,
		api_name="/run"
        #takes minimum of 30 seconds
)
print(result)

Setting Up Flux Space

import torch
from pipelines import DiffusionPipeline

base_model = "black-forest-labs/FLUX.1-dev"
pipe = DiffusionPipeline.from_pretrained(base_model, torch_dtype=torch.bfloat16)

lora_repo = "strangerzonehf/Flux-Super-Realism-LoRA"
trigger_word = "Super Realism"   #triggerword
pipe.load_lora_weights(lora_repo)

device = torch.device("cuda")
pipe.to(device)

Trigger words

[!WARNING] Trigger words: You should use Super Realism to trigger the image generation.

• —The trigger word is not mandatory; ensure that words like "realistic" and "realism" appear in the image description. The "super realism" trigger word should prompt an exact match to the reference image in the showcase.

Download model

Weights for this model are available in Safetensors format.

Download them in the Files & versions tab.