Instructions to use July66/julijxtm2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use July66/julijxtm2 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("July66/julijxtm2", 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 July66/julijxtm2: direct link, hf CLI and curl.
- Browser
- Download file 1.36 GB
-
https://huggingface.co/July66/julijxtm2/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://July66/julijxtm2/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/July66/julijxtm2/resolve/main/text_encoder/pytorch_model.bin
1.36 GB
- Xet hash:
- d444b671441e8ca477387f60eadba61b24ef08ec505984a385a13efe2187ad1d
- Size of remote file:
- 1.36 GB
- SHA256:
- 1082b3abff3c7eb6720e601e21b255431f2853253c064f68427074b7aec21646
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