Instructions to use Mujeeb603/lora-training with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Mujeeb603/lora-training 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("Mujeeb603/lora-training") prompt = "unconditional (blank prompt)" image = pipe(prompt).images[0] - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-1980/optimizer.bin from Mujeeb603/lora-training: direct link, hf CLI and curl.
- Browser
- Download file 28.5 MB
-
https://huggingface.co/Mujeeb603/lora-training/resolve/main/checkpoint-1980/optimizer.bin
- Command line
-
hf download hf://Mujeeb603/lora-training/checkpoint-1980/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/Mujeeb603/lora-training/resolve/main/checkpoint-1980/optimizer.bin
28.5 MB
- Xet hash:
- a564d5f04ffb8b101e4019983870ee66ceda13505a0377583c52233813fc293d
- Size of remote file:
- 28.5 MB
- SHA256:
- 5f16e46b0c1bfed4a2a196ffca5123bf863ae73648b2f423a5fd68261dc0bbba
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