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Ruolan Sun Claude Opus 4.8 commited on
Commit ·
3c37707
1
Parent(s): a525f5a
Fix demo: install from PyPI + correct model id and framing
Browse files- requirements: install pgmap-align==1.5.2 from PyPI (was git+...@v1.2.0,
the source of the build error)
- app.py: SD1.5 model id runwayml/stable-diffusion-v1-5 (removed/401) ->
stable-diffusion-v1-5/stable-diffusion-v1-5
- de-claim NeurIPS acceptance / drop "anonymous"; BibTeX @inproceedings -> @misc ;
README PyPI line -> pip install pgmap-align
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
- README.md +8 -7
- app.py +4 -4
- requirements.txt +3 -3
README.md
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@@ -8,16 +8,16 @@ sdk_version: 4.44.0
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app_file: app.py
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pinned: true
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license: mit
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short_description: PG-MAP inference-time alignment (NeurIPS 2026)
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---
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# PG-MAP Demo · NeurIPS 2026
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Interactive demo for **PG-MAP** (Preference-Guided Adaptive MAP) — a training-free framework that re-optimizes the conditioning $c$ and the latent $z_t$ at every denoising step. Supports SD 1.5, SDXL, and SD3.5-medium (UG-FM) backbones.
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- 🔗 **Paper** (NeurIPS 2026
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- 🤗 **Custom diffusers pipelines**: [pg-map-sd15](https://huggingface.co/sophialan/pg-map-sd15) · [pg-map-sdxl](https://huggingface.co/sophialan/pg-map-sdxl) · [pg-map-sd3](https://huggingface.co/sophialan/pg-map-sd3)
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- 📦 **PyPI**: `pip install
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## Hardware
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@@ -35,10 +35,11 @@ python app.py
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## Citation
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```bibtex
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@
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title={{PG-MAP}: Joint {MAP} Optimization for Inference-Time Alignment of Diffusion and Flow-Matching Models},
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author={Sun, Ruolan and Polak, Pawel},
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-
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}
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```
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app_file: app.py
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pinned: true
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license: mit
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short_description: PG-MAP inference-time alignment (NeurIPS 2026 submission)
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---
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# PG-MAP Demo · NeurIPS 2026 (under review)
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Interactive demo for **PG-MAP** (Preference-Guided Adaptive MAP) — a training-free framework that re-optimizes the conditioning $c$ and the latent $z_t$ at every denoising step. Supports SD 1.5, SDXL, and SD3.5-medium (UG-FM) backbones.
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- 🔗 **Paper** (preprint, under review at NeurIPS 2026): [github.com/sophialanlan/PG-MAP](https://github.com/sophialanlan/PG-MAP)
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- 🤗 **Custom diffusers pipelines**: [pg-map-sd15](https://huggingface.co/sophialan/pg-map-sd15) · [pg-map-sdxl](https://huggingface.co/sophialan/pg-map-sdxl) · [pg-map-sd3](https://huggingface.co/sophialan/pg-map-sd3)
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- 📦 **PyPI**: `pip install pgmap-align`
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## Hardware
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## Citation
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```bibtex
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@misc{sun2026pgmap,
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title={{PG-MAP}: Joint {MAP} Optimization for Inference-Time Alignment of Diffusion and Flow-Matching Models},
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author={Sun, Ruolan and Polak, Pawel},
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year={2026},
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note={Preprint; under review at NeurIPS 2026},
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url={https://github.com/sophialanlan/PG-MAP}
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}
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```
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app.py
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@@ -35,7 +35,7 @@ def _load(backbone: str):
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from diffusers import DiffusionPipeline
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spec = {
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"SD 1.5 (512²)": ("
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"SDXL (1024²)": ("stabilityai/stable-diffusion-xl-base-1.0","sophialan/pg-map-sdxl", {"variant": "fp16"}),
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"SD3.5-medium (1024²)": ("stabilityai/stable-diffusion-3.5-medium", "sophialan/pg-map-sd3", {}),
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}[backbone]
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@@ -111,13 +111,13 @@ def generate(prompt, backbone, seed, steps, guidance, lambda_reward, eta_z, K_in
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DESCRIPTION = """\
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# PG-MAP Demo · NeurIPS 2026
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**Inference-time alignment for diffusion + flow-matching** — re-optimize the
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conditioning $c$ and the latent $z_t$ at every denoising step under a
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trajectory-level Gibbs-MAP / proximal energy objective. No training required.
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🔗 Code: [github.com/sophialanlan/PG-MAP](https://github.com/sophialanlan/PG-MAP) · Paper:
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Pick a backbone, write a prompt, hit **Generate**. Toggle PG-MAP off to compare against the static baseline at the same seed. Default hyperparameters match the paper table; the sliders expose the productive ranges.
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"""
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def build_app():
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with gr.Blocks(title="PG-MAP Demo · NeurIPS 2026", theme=gr.themes.Soft()) as demo:
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gr.Markdown(DESCRIPTION)
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with gr.Row():
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with gr.Column(scale=2):
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from diffusers import DiffusionPipeline
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spec = {
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"SD 1.5 (512²)": ("stable-diffusion-v1-5/stable-diffusion-v1-5", "sophialan/pg-map-sd15", {}),
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"SDXL (1024²)": ("stabilityai/stable-diffusion-xl-base-1.0","sophialan/pg-map-sdxl", {"variant": "fp16"}),
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"SD3.5-medium (1024²)": ("stabilityai/stable-diffusion-3.5-medium", "sophialan/pg-map-sd3", {}),
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}[backbone]
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DESCRIPTION = """\
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# PG-MAP Demo · NeurIPS 2026 (under review)
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**Inference-time alignment for diffusion + flow-matching** — re-optimize the
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conditioning $c$ and the latent $z_t$ at every denoising step under a
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trajectory-level Gibbs-MAP / proximal energy objective. No training required.
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🔗 Code: [github.com/sophialanlan/PG-MAP](https://github.com/sophialanlan/PG-MAP) · Paper: preprint, under review at NeurIPS 2026 · HF Pipelines: [sd15](https://huggingface.co/sophialan/pg-map-sd15) · [sdxl](https://huggingface.co/sophialan/pg-map-sdxl) · [sd3](https://huggingface.co/sophialan/pg-map-sd3)
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Pick a backbone, write a prompt, hit **Generate**. Toggle PG-MAP off to compare against the static baseline at the same seed. Default hyperparameters match the paper table; the sliders expose the productive ranges.
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"""
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def build_app():
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with gr.Blocks(title="PG-MAP Demo · NeurIPS 2026 (under review)", theme=gr.themes.Soft()) as demo:
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gr.Markdown(DESCRIPTION)
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with gr.Row():
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with gr.Column(scale=2):
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requirements.txt
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@@ -1,5 +1,5 @@
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# Gradio Space dependencies. PG-MAP installs from the
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# pinned
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gradio>=4.0.0
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torch>=2.1.0
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torchvision>=0.16.0
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@@ -10,4 +10,4 @@ safetensors>=0.4.0
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open-clip-torch>=2.24.0
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numpy<2.0
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Pillow>=10.0.0
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# Gradio Space dependencies. PG-MAP installs from the published PyPI package
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# pinned at pgmap-align==1.5.2 so the demo behavior is reproducible.
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gradio>=4.0.0
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torch>=2.1.0
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torchvision>=0.16.0
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open-clip-torch>=2.24.0
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numpy<2.0
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Pillow>=10.0.0
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pgmap-align==1.5.2
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