Instructions to use Iman1/ida-version-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Iman1/ida-version-1 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Iman1/ida-version-1", 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
-
Upload sample_images with huggingface_hub
321a4d3 -
Upload model_index.json with huggingface_hub
199e118 -
Upload vae with huggingface_hub
78374b8 -
Upload unet with huggingface_hub
b0fd45c -
Upload tokenizer with huggingface_hub
9f81db9 -
Upload text_encoder with huggingface_hub
9cc1d03 -
Upload scheduler with huggingface_hub
15ad9f5 -
Upload safety_checker with huggingface_hub
b8817c5 -
Upload feature_extractor with huggingface_hub
3a518f7 -
Upload the concept Ida-version-1 embeds and token
bb4c616 -
initial commit
8516b6e