Instructions to use Jinl/DiffusionNFT-baselines with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Jinl/DiffusionNFT-baselines with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-3.5-medium", dtype=torch.bfloat16, device_map="cuda") pipe.load_lora_weights("Jinl/DiffusionNFT-baselines") 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
DiffusionNFT baselines
Logs and LoRA checkpoint artifacts for baseline experiments only. Rank-aware algorithm experiments are excluded.
Included runs:
nft_sd3_geneval_2026.04.20_11.18.57nft_sd3_geneval_2026.04.22_04.13.06
The archive contains 9 checkpoint directories and 703 source files (2.489 GiB before media compression; 2.488 GiB of published payload). These are adapters for Stable Diffusion 3.5 Medium, not the base model weights.
Provenance and checkpoint ownership
experiment_provenance.csv records the selected runs' saved Git commits,
configurations, and baseline classification.
The April 20 and April 22 runs record the upstream NVlabs/DiffusionNFT commit
cbb14f84b8312b620390dfcbe2fab69c1383b104, with principal hyperparameters matching
the upstream configuration. No working-tree snapshot or uncommitted diff was
saved, so a byte-for-byte pristine source tree cannot be proved.
Both runs recorded logs/nft/sd3/geneval as their checkpoint save directory.
That directory was later reused by the April 23 run. The timestamps of
logs/nft/sd3_v0/geneval/checkpoints/checkpoint-0 through checkpoint-240
(every 30 steps) align with the April 20 run, indicating a likely archived copy.
There is no explicit move record. These artifacts retain their original paths.
No separately identifiable April 22 checkpoints were found.
Contents
logs/nft_sd3_*/wandb/run-*/: W&B binary records, configs, summaries, output logs, environment records, and generated-media archives for the selected runs.logs/nft/sd3_v0/geneval/: the April 20-associated checkpoint archive, including LoRA, old-policy LoRA, optimizer state, and scaler state.artifact_manifest.jsonl: payload paths, sizes, SHA-256 values, and source-file counts.SHA256SUMS: checksums for all payload files.symlink_aliases.json: original convenience aliases; target files are included once instead of duplicatinglatest-runand debug-log aliases.
Download and extract
Use the Hugging Face CLI or huggingface_hub to download selected files.
Generated images are preserved losslessly in media.tar.zst next to their
original parent directory. With GNU tar and zstd installed:
sha256sum -c SHA256SUMS
tar --zstd -xf path/to/media.tar.zst -C path/to/parent
Run checksum verification from the repository root. Original local files were not modified. Credential-pattern scans were performed before publication; redaction counts, if any, are recorded in the manifest.
Upstream code: https://github.com/NVlabs/DiffusionNFT
Base model: https://huggingface.co/stabilityai/stable-diffusion-3.5-medium
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Model tree for Jinl/DiffusionNFT-baselines
Base model
stabilityai/stable-diffusion-3.5-medium