---
tags:
- text-to-image
- flux
- diffusers
- quantization
license: other
language:
- en
base_model:
- black-forest-labs/FLUX.1-dev
pipeline_tag: text-to-image
---

## Model Overview

`Silan10/flux_quantized_half` is a **half-precision (FP16) variant** of the
[`black-forest-labs/FLUX.1-dev`](https://huggingface.co/black-forest-labs/FLUX.1-dev)
text-to-image model. In this version, the **`transformers`**, **`text_encoder`** and
**`text_encoder_2`** folders have been converted to FP16.

This repository only changes the **numerical precision of the weights** to
`torch.float16` using PyTorch. This is not real quantization (like int8/int4). Still, 
converting the model to float16 saves memory, reduces RAM usage and speeds up loading times.

## Usage

```python
import torch
from diffusers import FluxPipeline

pipe = FluxPipeline.from_pretrained(
    "Silan10/flux_quantized_half",
    torch_dtype=torch.float16
)
pipe.to("cuda")  # or pipe.enable_model_cpu_offload() for low VRAM

prompt = "Close-up portrait photo of a standing 30 year old female with twin braids hairstyle."
image = pipe(
    prompt,
    guidance_scale=3.5,
    num_inference_steps=20,
    generator=torch.Generator("cpu").manual_seed(0)
).images[0]

image.save("flux_half_sample.png")