Instructions to use nematu/LORASGALA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use nematu/LORASGALA 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("nematu/LORASGALA") prompt = "yoIA PRUEBA1" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from nematu/LORASGALA: direct link, hf CLI and curl.
- Browser
- Download file 722 Bytes
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https://huggingface.co/nematu/LORASGALA/resolve/main/README.md
- Command line
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hf download hf://nematu/LORASGALA/README.md
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curl -L -o README.md https://huggingface.co/nematu/LORASGALA/resolve/main/README.md
722 Bytes
metadata
tags:
- flux
- text-to-image
- lora
- diffusers
- fal
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: yoIA PRUEBA1
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
LORASGALA
Model description
Trigger words
You should use yoIA PRUEBA1 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-lora-fast-training.