Instructions to use gababas/m3rrw3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use gababas/m3rrw3 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("gababas/m3rrw3", 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 gababas/m3rrw3: direct link, hf CLI and curl.
- Browser
- Download file 681 MB
-
https://huggingface.co/gababas/m3rrw3/resolve/main/text_encoder/pytorch_model.bin
- Command line
-
hf download hf://gababas/m3rrw3/text_encoder/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/gababas/m3rrw3/resolve/main/text_encoder/pytorch_model.bin
681 MB
- Xet hash:
- 4870576286378ada1c5e6132e863ff8749a9e669d151d3c850f1548bf74f29fc
- Size of remote file:
- 681 MB
- SHA256:
- 740d61bc4dbc293d96908a6078e982b7d7f3870bd26ec4be27ecf2b1a150ee83
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