Instructions to use seiya12/tunedmodel13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use seiya12/tunedmodel13 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/tunedmodel13", 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-500/optimizer.bin from seiya12/tunedmodel13: direct link, hf CLI and curl.
- Browser
- Download file 6.88 GB
-
https://huggingface.co/seiya12/tunedmodel13/resolve/main/checkpoint-500/optimizer.bin
- Command line
-
hf download hf://seiya12/tunedmodel13/checkpoint-500/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/seiya12/tunedmodel13/resolve/main/checkpoint-500/optimizer.bin
6.88 GB
- Xet hash:
- 86fa2e0bcdfb41ec100122cb64131a7dfa881dd1a472c2fa7db31eca4c01fdb5
- Size of remote file:
- 6.88 GB
- SHA256:
- ba4bb8a834d714b4c319add7de14232c2ce54561e0f285491d3972eb3e9963ea
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