Instructions to use DeepFloyd/IF-I-XL-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use DeepFloyd/IF-I-XL-v1.0 with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("DeepFloyd/IF-I-XL-v1.0", 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
- Draw Things
- DiffusionBee
Running the notebook gives OutOfMemory Error on a RTX 3090 24GB Card
#10
by notune - opened
When running the notebook pipes-DeepFloyd-IF-v1.0.ipynb, I get OutOfMemoryError: CUDA out of memory. Tried to allocate 320.00 MiB (GPU 0; 24.00 GiB total capacity; 22.54 GiB already allocated; 0 bytes free; 22.93 GiB reserved in total by PyTorch) If reserved memory is >> allocated memory try setting max_split_size_mb to avoid fragmentation. See documentation for Memory Management and PYTORCH_CUDA_ALLOC_CONF even tho I thought 24Gig cards are supported
notune changed discussion status to closed