Instructions to use fspecii/anm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use fspecii/anm with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("black-forest-labs/FLUX.1-dev", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("fspecii/anm") prompt = "anm amb in park" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
metadata
tags:
- text-to-image
- flux
- lora
- diffusers
- template:sd-lora
- fluxgym
widget:
- output:
url: sample/anm_002500_00_20250713221352.png
text: anm amb in park
- output:
url: sample/anm_002500_01_20250713221358.png
text: anm drp in the garden
- output:
url: sample/anm_002500_02_20250713221405.png
text: anm drp and amb in a forest
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: anm
license: other
license_name: flux-1-dev-non-commercial-license
license_link: https://huggingface.co/black-forest-labs/FLUX.1-dev/blob/main/LICENSE.md
anm
A Flux LoRA trained on a local computer with Fluxgym

- Prompt
- anm amb in park

- Prompt
- anm drp in the garden

- Prompt
- anm drp and amb in a forest
Trigger words
You should use anm to trigger the image generation.
Download model and use it with ComfyUI, AUTOMATIC1111, SD.Next, Invoke AI, Forge, etc.
Weights for this model are available in Safetensors format.