Instructions to use sagata007/ram with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sagata007/ram 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("sagata007/ram") prompt = "-" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
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Download README.md from sagata007/ram: direct link, hf CLI and curl.
- Browser
- Download file 455 Bytes
-
https://huggingface.co/sagata007/ram/resolve/main/README.md
- Command line
-
hf download hf://sagata007/ram/README.md
-
curl -L -o README.md https://huggingface.co/sagata007/ram/resolve/main/README.md
455 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- output:
url: images/94d45349-9dcd-47f1-9605-3ff950b98324.jpg
text: '-'
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: KRSU_MIDA_MARCH394898
ram

- Prompt
- -
Trigger words
You should use KRSU_MIDA_MARCH394898 to trigger the image generation.
Download model
Download them in the Files & versions tab.