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-5000/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-5000/pytorch_model.bin
- Command line
-
hf download hf://tangjs/tex-lora/checkpoint-5000/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tangjs/tex-lora/resolve/main/checkpoint-5000/pytorch_model.bin
102 MB
- Xet hash:
- b3444a826d2e02d47f9e81ae6e1f4d6a9d37bb40013ee82b3128e23011b02cbf
- Size of remote file:
- 102 MB
- SHA256:
- 45aac7eb4f4c667265161467cb03c8000a0baaa6ac739428a681894e7245e97d
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