Instructions to use JingyeChen22/textdiffuser2-lora-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use JingyeChen22/textdiffuser2-lora-ft with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("JingyeChen22/textdiffuser2-lora-ft", 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
- Local Apps Settings
- Draw Things
- DiffusionBee
Download pytorch_model.bin from JingyeChen22/textdiffuser2-lora-ft: direct link, hf CLI and curl.
- Browser
- Download file 3.29 MB
-
https://huggingface.co/JingyeChen22/textdiffuser2-lora-ft/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://JingyeChen22/textdiffuser2-lora-ft/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/JingyeChen22/textdiffuser2-lora-ft/resolve/main/pytorch_model.bin
3.29 MB
- Xet hash:
- 67975f40716084ca0665c34d023617caa699853ef456f8207a3f03ca5d5a3775
- Size of remote file:
- 3.29 MB
- SHA256:
- 4d2c504ba97a3b225f55037882adde51541c006afb0ab816d532a1585e5b363b
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