Instructions to use michealscott/trained_flux_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use michealscott/trained_flux_2 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("michealscott/trained_flux_2") prompt = "SAREEGEN" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from michealscott/trained_flux_2: direct link, hf CLI and curl.
- Browser
- Download file 606 Bytes
-
https://huggingface.co/michealscott/trained_flux_2/resolve/main/README.md
- Command line
-
hf download hf://michealscott/trained_flux_2/README.md
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curl -L -o README.md https://huggingface.co/michealscott/trained_flux_2/resolve/main/README.md
606 Bytes
metadata
tags:
- flux
- text-to-image
- lora
- diffusers
- fal
base_model: undefined
instance_prompt: SAREEGEN
license: other
trained_flux_2
Model description
flux 2 trained on saree for 2000 steps
Trigger words
You should use SAREEGEN 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/flux-2-trainer/edit.