Instructions to use tangjs/tex-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use tangjs/tex-lora with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("tangjs/tex-lora") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Download checkpoint-1500/scheduler.bin from tangjs/tex-lora: direct link, hf CLI and curl.
- Browser
- Download file 559 Bytes
-
https://huggingface.co/tangjs/tex-lora/resolve/main/checkpoint-1500/scheduler.bin
- Command line
-
hf download hf://tangjs/tex-lora/checkpoint-1500/scheduler.bin
-
curl -L -o scheduler.bin https://huggingface.co/tangjs/tex-lora/resolve/main/checkpoint-1500/scheduler.bin
559 Bytes
- Xet hash:
- 23d5cac6dbf52abed22ec7ee1a0c48eaec2468015bf7e4c37c51557eb8118a9e
- Size of remote file:
- 559 Bytes
- SHA256:
- b59411fc8d42bec7e425fddec0aa3882f60cee12ebdf22b3ceab7e5a62c1c065
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