Instructions to use Falah/spacemidj with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Falah/spacemidj with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Falah/spacemidj", 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
Commit History
-
Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (#2)
- Fix deprecation warning by changing `CLIPFeatureExtractor` to `CLIPImageProcessor`. (caf3e81c94d589f15e0a2f64ec356c7df5c21083)624125c
-
update
40f616e -
Upload sample_images with huggingface_hub
83b391c -
Upload model_index.json with huggingface_hub
0b2083d -
Upload vae with huggingface_hub
55ea622 -
Upload unet with huggingface_hub
999f669 -
Upload tokenizer with huggingface_hub
50ec514 -
Upload text_encoder with huggingface_hub
5fcfb6e -
Upload scheduler with huggingface_hub
0e275c3 -
Upload safety_checker with huggingface_hub
e769429 -
Upload feature_extractor with huggingface_hub
200793c -
Upload the concept spacemidj embeds and token
5282cca -
initial commit
2edcf5f