Instructions to use rando2625/model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use rando2625/model with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("rando2625/model") prompt = "a photo of sks megumi" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-300/optimizer.bin from rando2625/model: direct link, hf CLI and curl.
- Browser
- Download file 6.59 MB
-
https://huggingface.co/rando2625/model/resolve/main/checkpoint-300/optimizer.bin
- Command line
-
hf download hf://rando2625/model/checkpoint-300/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/rando2625/model/resolve/main/checkpoint-300/optimizer.bin
6.59 MB
- Xet hash:
- 67fec586e4f334a63010284ee9bd1e3e6ac01072faa019a81199eab8bf26e214
- Size of remote file:
- 6.59 MB
- SHA256:
- 384c12ad3280222f65039299e3efb964297f578a832eee78de6694a4799113e6
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