---
title: flux-trolley-problem
canonical_url: "https://www.modelscope.cn/models/fofr/flux-trolley-problem"
md_url: "https://www.modelscope.cn/models/fofr/flux-trolley-problem.md"
repository: fofr/flux-trolley-problem
last_updated: 2024-12-22
license: other
pipeline_tag: text-to-image-synthesis
tasks:
  - text-to-image-synthesis
base_model:
  - black-forest-labs/FLUX.1-dev
base_model_relation: adapter
parameters: 85.9M
tensor_type:
  - F16
library_name:
  - pytorch
  - diffusers
  - lora
  - safetensors
frameworks:
  - pytorch
language:
  - en
downloads: 1128
stars: 0
tags:
  - flux
  - diffusers
  - lora
  - replicate
---

# flux-trolley-problem

> flux-trolley-problem - fofr 在 ModelScope 开源的模型。Flux Trolley Problem

fofr/flux-trolley-problem 是 ModelScope 魔搭社区上的 85.9M 参数text-to-image-synthesis模型，采用 other 许可，基于 black-forest-labs/FLUX.1-dev 构建。

- **Repository**: fofr/flux-trolley-problem
- **License**: other
- **Tasks**: text-to-image-synthesis
- **Parameters**: 85.9M
- **Base model**: black-forest-labs/FLUX.1-dev
- **Tags**: flux, diffusers, lora, replicate
- **Downloads**: 1128
- **Stars**: 0
- **Last updated**: 2024-12-22

Source: https://www.modelscope.cn/models/fofr/flux-trolley-problem

---

# Flux Trolley Problem

<Gallery />

Trained on Replicate using:

https://replicate.com/ostris/flux-dev-lora-trainer/train


## Trigger words
You should use `TROLLEY_PROBLEM` to trigger the image generation.


## Use it with the [🧨 diffusers library](https://github.com/huggingface/diffusers)

```py
from diffusers import AutoPipelineForText2Image
import torch

pipeline = AutoPipelineForText2Image.from_pretrained('black-forest-labs/FLUX.1-dev', torch_dtype=torch.float16).to('cuda')
pipeline.load_lora_weights('fofr/flux-trolley-problem', weight_name='lora.safetensors')
image = pipeline('your prompt').images[0]
```

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)