Instructions to use BreakpointAI/socknetq with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use BreakpointAI/socknetq with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("BreakpointAI/socknetq", 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
Download conf_weighter.pth from BreakpointAI/socknetq: direct link, hf CLI and curl.
- Browser
- Download file 2 kB
-
https://huggingface.co/BreakpointAI/socknetq/resolve/main/conf_weighter.pth
- Command line
-
hf download hf://BreakpointAI/socknetq/conf_weighter.pth
-
curl -L -o conf_weighter.pth https://huggingface.co/BreakpointAI/socknetq/resolve/main/conf_weighter.pth
2 kB
- Xet hash:
- ef186b9061462c086f9736e454e2f228779cee8c43b95be82d9ec55ba1d2c75d
- Size of remote file:
- 2 kB
- SHA256:
- cf425cc65679a61911bcd0c04fbf4029e063f096581aa9f422385cc8ab175505
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