Instructions to use sergiocannata/diffuser_generated_mam_CBIS_benign_128x128 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use sergiocannata/diffuser_generated_mam_CBIS_benign_128x128 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("sergiocannata/diffuser_generated_mam_CBIS_benign_128x128", 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 checkpoint-2000/optimizer.bin from sergiocannata/diffuser_generated_mam_CBIS_benign_128x128: direct link, hf CLI and curl.
- Browser
- Download file 910 MB
-
https://huggingface.co/sergiocannata/diffuser_generated_mam_CBIS_benign_128x128/resolve/main/checkpoint-2000/optimizer.bin
- Command line
-
hf download hf://sergiocannata/diffuser_generated_mam_CBIS_benign_128x128/checkpoint-2000/optimizer.bin
-
curl -L -o optimizer.bin https://huggingface.co/sergiocannata/diffuser_generated_mam_CBIS_benign_128x128/resolve/main/checkpoint-2000/optimizer.bin
910 MB
- Xet hash:
- ee81b91e8d1885fa269388e8ad6396e20bd190ab915925f97e097c69bbdd5c01
- Size of remote file:
- 910 MB
- SHA256:
- a113a360e5d363f7fc342fe7ffadc7ab1f351dcb63367ac919920d983d0df587
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