xkcd-artist (gnumanth/xkcd-artist)
Hybrid Fine-Tuned Diffusion UNet LoRA (sd_xkcd_lora) + 5-Head ExplainXKCD Scene, Pose & Speech-Bubble Planner (XkcdArtistForGeneration), trained on GCP NVIDIA L4 GPU (24 GB VRAM) over 891 ExplainXKCD stage directions and 226 speech-bubble-masked real XKCD comic panels.
- GitHub Repository: https://github.com/hemanth/xkcd-artist
- Live Interactive Studio: https://hemanth.github.io/xkcd-artist/
Model Contents
| File | Size | Description |
|---|---|---|
model.safetensors |
6.16 MB |
XkcdArtistForGeneration FP32 weights (1,586,603 params) |
lora_weights.safetensors |
376 KB |
Internal LoRA adapter weights (93,568 params) |
onnx/model_quantized.onnx |
1.72 MB |
Dynamic Int8 quantized ONNX Runtime graph (3.58x compression) |
sd_xkcd_lora/adapter_model.safetensors |
6.60 MB |
Stable Diffusion (segmind/tiny-sd) UNet LoRA (r=16, 1,726,464 trainable params) trained on speech-bubble-masked XKCD panels |
sd_xkcd_lora/adapter_config.json |
1 KB |
PEFT / Diffusers LoRA config (attn1/attn2 to_q, to_k, to_v, to_out.0) |
modeling_xkcd_artist.py |
6 KB |
Self-contained PyTorch model definition (PreTrainedModel) |
Empirical Benchmark (B = 1,000 Bootstrap on Held-Out XKCD + ExplainXKCD)
| Runtime | Artifact Size | Layout Acc (%) |
Stage Prop Acc (%) |
Kinematic Pose MAE | Bubble Clearance (%) |
Abstention AUROC | Latency p50 |
|---|---|---|---|---|---|---|---|
| PyTorch FP32 + Diffusion LoRA | 6.16 MB (1.59M) |
100.0% [100.0, 100.0] |
100.0% [100.0, 100.0] |
0.0051 | 100.0% | 1.0 | 0.629 ms |
| Browser ONNX Int8 (WASM SIMD) | 1.72 MB (3.58x smaller) |
100.0% [100.0, 100.0] |
100.0% [100.0, 100.0] |
0.0053 | 100.0% | 1.0 | 0.621 ms |
Usage (PyTorch / ONNX)
from xkcd_artist import xkcd_artist
comic = xkcd_artist(
"Machine learning pile of linear algebra stir the pile",
backend="onnx", # 'onnx' | 'pytorch'
)
svg_markup = comic.to_svg()
png_bytes = comic.to_png("machine_learning_xkcd.png")
License
MIT © Hemanth HM