Instructions to use cuongdev/7-nguoi-8500-new with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use cuongdev/7-nguoi-8500-new with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("cuongdev/7-nguoi-8500-new", 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 cuongdev/7-nguoi-8500-new: direct link, hf CLI and curl.
- Browser
- Download file 681 MB
-
https://huggingface.co/cuongdev/7-nguoi-8500-new/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://cuongdev/7-nguoi-8500-new/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/cuongdev/7-nguoi-8500-new/resolve/main/text_encoder/pytorch_model.bin
681 MB
- Xet hash:
- 9bfbf3a824db5bca77ddb22aad1f1f9c81a180100a935a3b186f42c3becf2a32
- Size of remote file:
- 681 MB
- SHA256:
- 3c24d09b898cbcfb495b4a1359a5f114b0a626591de6010c55be7cab2702a793
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