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---
license: creativeml-openrail-m
tags:
- imagepipeline
- imagepipeline.io
- text-to-image
- ultra-realistic
- lora
pinned: false
pipeline_tag: text-to-image
base_model:
- black-forest-labs/FLUX.1-dev
new_version: black-forest-labs/FLUX.1-dev
library_name: diffusers
widget:
- text: A detailed photograph of a woman with short brunette hair styled in a sleek bob haircut. She is wearing a spaghetti strap, form-fitting sequin dress that shimmers in the light, sipping champagne from a glass at an elegant bar. Her makeup is flawless, featuring glossy lipstick, smoky eyes, and perfect, striking features.
output:
url: images/ip-realism.png
---
## Flux_Realism_Super_Lora
<img src="" alt="Generated on Image Pipeline" style="border-radius: 10px;">
**This lora model is uploaded on [imagepipeline.io](https://imagepipeline.io/)**
Model details -
[](https://imagepipeline.io/models/Flux_Realism_Super_Lora?id=fd8813ee-307a-4ca3-b4b5-e9a480d89069/)
## How to try this model ?
You can try using it locally or send an API call to test the output quality.
Get your `API_KEY` from [imagepipeline.io](https://imagepipeline.io/). No payment required.
Coding in `php` `javascript` `node` etc ? Checkout our documentation
[](https://docs.imagepipeline.io/docs/introduction)
```python
import requests
import json
url = "https://imagepipeline.io/generate/v3"
payload = json.dumps({
"prompt": ""A detailed photograph of a woman with short brunette hair styled in a sleek bob haircut. She is wearing a spaghetti strap, form-fitting sequin dress that shimmers in the light, sipping champagne from a glass at an elegant bar. Her makeup is flawless, featuring glossy lipstick, smoky eyes, and perfect, striking features. The atmosphere is moody and sophisticated, with bluish ambient lighting casting soft shadows and enhancing the glamour of the scene."
"width": "1024",
"height": "1024",
"samples": "1",
"num_inference_steps": "20",
"lora_models": ["fd8813ee-307a-4ca3-b4b5-e9a480d89069"],
"lora_weights": ["0.5"]
})
headers = {
'Content-Type': 'application/json',
'API-Key': 'your_api_key'
}
response = requests.request("POST", url, headers=headers, data=payload)
print(response.text)
}
```
Get more ready to use `MODELS` like this for `SD 1.5` and `SDXL` and `FLUX`:
[](https://imagepipeline.io/models)
### API Reference
#### Generate Image
```http
https://api.imagepipeline.io/generate/v3
```
| Headers | Type | Description |
|:----------------------| :------- |:-------------------------------------------------------------------------------------------------------------------|
| `API-Key` | `str` | Get your `API_KEY` from [imagepipeline.io](https://imagepipeline.io/) |
| `Content-Type` | `str` | application/json - content type of the request body |
| Parameter | Type | Description |
| :-------- | :------- | :------------------------- |
| `model_id` | `str` | Your base model, find available lists in [models page](https://imagepipeline.io/models) or upload your own|
| `prompt` | `str` | Text Prompt. Check our [Prompt Guide](https://docs.imagepipeline.io/docs/SD-1.5/docs/extras/prompt-guide) for tips |
| `num_inference_steps` | `int [1-50]` | Noise is removed with each step, resulting in a higher-quality image over time. Ideal value 30-50 (without LCM) |
| `guidance_scale` | `float [1-20]` | Higher guidance scale prioritizes text prompt relevance but sacrifices image quality. Ideal value 7.5-12.5 |
| `lora_models` | `str, array` | Pass the model_id(s) of LoRA models that can be found in models page |
| `lora_weights` | `str, array` | Strength of the LoRA effect |
---
license: creativeml-openrail-m
tags:
- imagepipeline
- imagepipeline.io
- text-to-image
- ultra-realistic
pinned: false
pipeline_tag: text-to-image
---
### Feedback
If you have any feedback, please reach out to us at [email protected]
#### 🔗 Visit Website
[](https://imagepipeline.io/)
If you are the original author of this model, please [click here](https://airtable.com/apprTaRnJbDJ8ufOx/shr4g7o9B6fWfOlUR) to add credits |