Instructions to use HuggingSelf/test0519 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Bagel
How to use HuggingSelf/test0519 with Bagel:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
Add Unified-Bench old protocol bundle: unified_bench_old_protocol_0p8346/README.md
Browse files
unified_bench_old_protocol_0p8346/README.md
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# Unified-Bench old protocol reproduction bundle
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This folder contains the assets used to reproduce the historical raw BAGEL
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Unified-Bench score `0.8345940754981711` under the old TorchUMM protocol.
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HF path prefix:
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```text
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HuggingSelf/test0519/unified_bench_old_protocol_0p8346
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```
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## Contents
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- `inputs/unified_bench/Image/`: the 100 Unified-Bench reference input images.
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- `outputs/raw_bagel/images/`: raw BAGEL round-trip generated images.
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- `outputs/raw_bagel/captions.jsonl`: image-to-text captions produced by raw BAGEL.
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- `outputs/raw_bagel/summary.json`: original old-protocol score JSON.
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- `scorers/dinov3-vitl16_old_protocol/`: the old DINOv3 scorer checkpoint used by the historical run.
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- `configs/unified_bench_bagel.yaml`: old TorchUMM Unified-Bench config.
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- `scripts/reproduce_apr4_unified_bagel_score.py`: Modal-side reproduction helper used to verify the score.
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- `scripts/run_scoring.py` and `scripts/scorers/`: scoring code snapshot from TorchUMM.
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- `manifest.json`: hashes, counts, paths, and expected scores.
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## Expected Score
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| scorer | average |
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| --- | ---: |
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| CLIP | 0.894650644659996 |
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| DINOv2 | 0.787667881194502 |
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| DINOv3 old protocol | 0.723970373794436 |
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| LongCLIP | 0.932087402343750 |
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| Overall | 0.834594075498171 |
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Overall is the mean of the four scorer averages.
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## DINOv3
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Old-protocol DINOv3 file:
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```text
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scorers/dinov3-vitl16_old_protocol/model.safetensors
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```
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Expected SHA256:
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```text
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dcb2e45127cccbf1601e5f42fef165eea275c8e5213197e8dcf3f48822718179
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```
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The newer cached DINOv3 weight we tested separately produced very high
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reference-to-reference similarity and should not be mixed with this old
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protocol score.
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## Reproduction Notes
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The historical run was verified on Modal workspace `aifrontierwm` using:
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```text
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ref_dir = /datasets/unified_bench/Image
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gen_dir = /output-apr4/unified_bench/bagel/images
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```
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Scoring model paths:
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```text
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clip = /model_cache/unified_bench/clip-vit-large-patch14
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dinov2 = /model_cache/unified_bench/dinov2-large
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dinov3 = /model_cache/unified_bench/dinov3-vitl16
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longclip = /model_cache/unified_bench/longclip-L.pt
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```
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The bundle includes the old DINOv3 directory because this is the piece that made
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the old protocol reproducible. CLIP, DINOv2, and LongCLIP are public/downloadable
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from the sources listed in `manifest.json`.
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## Minimal Download Example
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```python
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from huggingface_hub import snapshot_download
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root = snapshot_download(
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repo_id="HuggingSelf/test0519",
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repo_type="model",
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allow_patterns=["unified_bench_old_protocol_0p8346/**"],
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)
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print(root)
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```
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After downloading, point TorchUMM's Unified-Bench scorer at:
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```text
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ref_dir: <download_root>/unified_bench_old_protocol_0p8346/inputs/unified_bench/Image
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out_dir: <download_root>/unified_bench_old_protocol_0p8346/outputs/raw_bagel
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dinov3: <download_root>/unified_bench_old_protocol_0p8346/scorers/dinov3-vitl16_old_protocol
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```
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