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-1000/pytorch_model.bin from tangjs/tex-lora: direct link, hf CLI and curl.
- Browser
- Download file 102 MB
-
https://huggingface.co/tangjs/tex-lora/resolve/main/checkpoint-1000/pytorch_model.bin
- Command line
-
hf download hf://tangjs/tex-lora/checkpoint-1000/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tangjs/tex-lora/resolve/main/checkpoint-1000/pytorch_model.bin
102 MB
- Xet hash:
- 4a581d8f154969369f8a7b0a31c70cc0b74b7a32928c0a95e8e61de19e9d72bd
- Size of remote file:
- 102 MB
- SHA256:
- 543514e379938b3ac561ba5aaccc066ccc8be012a298c19e427f331ceff718df
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