import torch
from diffusers import DiffusionPipeline
# switch to "mps" for apple devices
pipe = DiffusionPipeline.from_pretrained("sjmathy/scare", dtype=torch.bfloat16, device_map="cuda")
prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k"
image = pipe(prompt).images[0]YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
Vidar Priority27 RoboTwin Training Bundle
This bundle is self-contained for cached-latent LoRA training.
Contents:
code/vidar: Vidar/Wan training code.data/robotwin_priority27_varcond_cache: portableindex.csv, cached latents, cached text embeddings.models/vidar/vidar.pt: Vidar initialization.models/Wan2.2-TI2V-5B: base Wan checkpoint. Included: True.- Source videos included for debugging/provenance: False.
Training uses --use_latent_cache, so source videos are not needed for the training dataloader.
Run:
cd /path/to/vidar_priority27_train_bundle_20260426
bash train_priority27_cached_lora.sh /path/to/output
If using Slurm, adapt scripts/sbatch_train_robotwin_priority27_single121_varcond_*.sh
to your cluster's partition/GPU flags and point paths inside this bundle.
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