Instructions to use ACCC1380/realstyle2_anima with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use ACCC1380/realstyle2_anima with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("circlestone-labs/Anima", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("ACCC1380/realstyle2_anima") 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 scripts/run_train.sh from ACCC1380/realstyle2_anima: direct link, hf CLI and curl.
- Browser
- Download file 596 Bytes
-
https://huggingface.co/ACCC1380/realstyle2_anima/resolve/main/scripts/run_train.sh
- Command line
-
hf download hf://ACCC1380/realstyle2_anima/scripts/run_train.sh
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curl -L -o run_train.sh https://huggingface.co/ACCC1380/realstyle2_anima/resolve/main/scripts/run_train.sh
596 Bytes
| set -euo pipefail | |
| export PATH="/data/venv-training/bin:$PATH" | |
| export HF_HOME=/data/realstyle2/cache/huggingface | |
| export HF_ENDPOINT=https://huggingface.co | |
| # The /data volume cannot host Unix-domain sockets required by multiprocessing. | |
| # Only transient IPC uses /tmp; datasets, caches, code, logs and output stay /data. | |
| export TMPDIR=/tmp | |
| export PYTHONUNBUFFERED=1 | |
| export OMP_NUM_THREADS=4 | |
| export TOKENIZERS_PARALLELISM=false | |
| export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True | |
| cd /data/lora-scripts-next | |
| exec bash train_anima_by_toml.sh /data/realstyle2/configs/train.toml | |