Instructions to use seiya12/tunedmodel5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use seiya12/tunedmodel5 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("seiya12/tunedmodel5", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download checkpoint-2000/optimizer.bin from seiya12/tunedmodel5: direct link, hf CLI and curl.
- Browser
- Download file 6.88 GB
-
https://huggingface.co/seiya12/tunedmodel5/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://seiya12/tunedmodel5/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/seiya12/tunedmodel5/resolve/main/checkpoint-2000/optimizer.bin
6.88 GB
- Xet hash:
- 4028161e19a0bc496646677db2a3fee3000af2553ccab176a51ccf5fbd9b0781
- Size of remote file:
- 6.88 GB
- SHA256:
- 378b50421caa7d1bcbf7e7929f7f8015270b8ace35babe37578768001070d61b
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