Instructions to use zhoubinjason/first-avartar with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use zhoubinjason/first-avartar with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("zhoubinjason/first-avartar", 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 zhoubinjason/first-avartar: direct link, hf CLI and curl.
- Browser
- Download file 492 MB
-
https://huggingface.co/zhoubinjason/first-avartar/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://zhoubinjason/first-avartar/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/zhoubinjason/first-avartar/resolve/main/text_encoder/pytorch_model.bin
492 MB
- Xet hash:
- 431ddd21acdaec9027b0b050e7abae915f24ca1203bd18c2508858bbd5cbe010
- Size of remote file:
- 492 MB
- SHA256:
- 387577197a1c1a17927dc92134f1cd9cbe06a7e6d228ecca767d095b19a3a287
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