Instructions to use Zackfalcondev/befamoos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Zackfalcondev/befamoos with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("undefined", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Zackfalcondev/befamoos") prompt = "ohwx" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from Zackfalcondev/befamoos: direct link, hf CLI and curl.
- Browser
- Download file 560 Bytes
-
https://huggingface.co/Zackfalcondev/befamoos/resolve/main/README.md
- Command line
-
hf download hf://Zackfalcondev/befamoos/README.md
-
curl -L -o README.md https://huggingface.co/Zackfalcondev/befamoos/resolve/main/README.md
560 Bytes
metadata
tags:
- flux
- text-to-image
- lora
- diffusers
- fal
base_model: undefined
instance_prompt: ohwx
license: other
befamoos
Model description
Model Illanah
Trigger words
You should use ohwx to trigger the image generation.
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.
Training at fal.ai
Training was done using fal.ai/models/fal-ai/turbo-flux-trainer.