---
base_model: black-forest-labs/FLUX.1-schnell
license: apache-2.0
language:
- en
- pt
- th
library_name: diffusers
pipeline_tag: text-to-image
tags:
- UnfilteredAI
- 3d
- text-to-image
- not-for-all-audiences
---

**Model Name:** UnfilteredAI/NSFW-Flux-v1 🚀

**Type:** Text-to-Image Generator
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**Description:** **Description:** 

**NSFW-Flux-v1** is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. Finetuned by **UnfilteredAI**, this model is designed to produce a wide range of images, including explicit and NSFW (Not Safe For Work) images from textual inputs. Whether you're looking for artistic, realistic, or fantastical imagery, NSFW-Flux-v1 has got you covered! 🌟

**Features:**
- **🖼️ Uncensored Output:** The model generates uncensored and potentially explicit images based on textual inputs, providing complete creative freedom.
- **⚡ Tensor Type:** Utilizes BF16 tensor type for optimized performance and efficiency, ensuring quick and smooth generation.
- **💪 Model Size:** With 12 billion parameters, NSFW-Flux-v1 offers an extensive capacity for learning and generating diverse and detailed imagery.
- **🌀 3D Style Rendering:** Enhanced with 3D style/image rendering capability to create more lifelike and dynamic images. (Use "3d", "3d style" in your prompt)
- **🔄 Continuous Improvement:** The model is continually updated and refined to improve its performance and expand its capabilities.

**Usage Guidelines:**
- **🛡️ Responsible Use:** Exercise discretion and responsibility when generating content with this model. The nature of the content generated can be explicit, so use it wisely.
- **👥 Age Restriction:** Due to the explicit nature of the generated content, usage is restricted to individuals over the legal age in their jurisdiction. Ensure compliance with local laws and regulations.


```python
import torch
from diffusers import FluxPipeline

pipe = FluxPipeline.from_pretrained("UnfilteredAI/NSFW-Flux-v1", torch_dtype=torch.bfloat16)
pipe.enable_model_cpu_offload() #save some VRAM by offloading the model to CPU. Remove this if you have enough GPU power

prompt = "A cat holding a sign that says hello world"
image = pipe(
    prompt,
    guidance_scale=0.0,
    num_inference_steps=4,
    max_sequence_length=256,
    generator=torch.Generator("cpu").manual_seed(0)
).images[0]
image.save("NSFW-Flux-v1.png")
```