Instructions to use here4code/Myself with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use here4code/Myself 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("here4code/Myself") 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 here4code/Myself: direct link, hf CLI and curl.
- Browser
- Download file 402 Bytes
-
https://huggingface.co/here4code/Myself/resolve/e6197ff99d316d4c0983c9414b042d6b7aaa8b3c/README.md
- Command line
-
hf download hf://here4code/Myself@e6197ff99d316d4c0983c9414b042d6b7aaa8b3c/README.md
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curl -L -o README.md https://huggingface.co/here4code/Myself/resolve/e6197ff99d316d4c0983c9414b042d6b7aaa8b3c/README.md
402 Bytes
metadata
tags:
- text-to-image
- lora
- diffusers
- template:diffusion-lora
widget:
- text: '-'
output:
url: images/829066140249650699.png
base_model: black-forest-labs/FLUX.1-dev
instance_prompt: null
license: apache-2.0
v1

- Prompt
- -
Download model
Weights for this model are available in Safetensors format.
Download them in the Files & versions tab.