Instructions to use gfalcao/ldsct7 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gfalcao/ldsct7 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("gfalcao/ldsct7", 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 text_encoder/pytorch_model.bin from gfalcao/ldsct7: direct link, hf CLI and curl.
- Browser
- Download file 681 MB
-
https://huggingface.co/gfalcao/ldsct7/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://gfalcao/ldsct7/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gfalcao/ldsct7/resolve/main/text_encoder/pytorch_model.bin
681 MB
- Xet hash:
- 789050878cf6529963fd192b3f353a12fd128f9ed93829c0c31b48c3f6098dcc
- Size of remote file:
- 681 MB
- SHA256:
- 4df8de8eb8404b48dc77aff0737d030f17dedde64692db2cc31fb55790eb2ea9
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