Add metadata (license, pipeline tag, library name) to model card
#1
by
nielsr
HF Staff
- opened
README.md
CHANGED
|
@@ -1,3 +1,9 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
# Model Card for HP (High-Preference) Model
|
| 2 |
|
| 3 |
This model is a specialized human preference scoring function that evaluates image quality based purely on visual aesthetics and human preferences, without relying on text-image alignment. See our paper [Enhancing Reward Models for High-quality Image Generation: Beyond Text-Image Alignment](https://arxiv.org/abs/2507.19002) for more details.
|
|
@@ -12,16 +18,16 @@ The HP (High-Preference) model represents a paradigm shift in image quality eval
|
|
| 12 |
|
| 13 |
### Key Features
|
| 14 |
|
| 15 |
-
-
|
| 16 |
-
-
|
| 17 |
-
-
|
| 18 |
|
| 19 |
### Model Sources
|
| 20 |
|
| 21 |
-
*
|
| 22 |
-
*
|
| 23 |
-
*
|
| 24 |
-
*
|
| 25 |
|
| 26 |
## How to Get Started with the Model
|
| 27 |
|
|
@@ -102,4 +108,4 @@ This model was trained on 36000 preference triplets from [Pick-High datase](http
|
|
| 102 |
primaryClass={cs.CV},
|
| 103 |
url={https://arxiv.org/abs/2507.19002},
|
| 104 |
}
|
| 105 |
-
```
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
pipeline_tag: image-feature-extraction
|
| 4 |
+
library_name: transformers
|
| 5 |
+
---
|
| 6 |
+
|
| 7 |
# Model Card for HP (High-Preference) Model
|
| 8 |
|
| 9 |
This model is a specialized human preference scoring function that evaluates image quality based purely on visual aesthetics and human preferences, without relying on text-image alignment. See our paper [Enhancing Reward Models for High-quality Image Generation: Beyond Text-Image Alignment](https://arxiv.org/abs/2507.19002) for more details.
|
|
|
|
| 18 |
|
| 19 |
### Key Features
|
| 20 |
|
| 21 |
+
- **Image-Only Evaluation**: No text input required, focuses purely on visual quality
|
| 22 |
+
- **Human Preference Aligned**: Trained on preference triplets from [Pick-High datase](https://huggingface.co/datasets/8y/Pick-High-Dataset) and Pick-a-pic dataset
|
| 23 |
+
- **Complementary Design**: Works optimally when combined with [ICT model](https://huggingface.co/8y/ICT) for comprehensive evaluation
|
| 24 |
|
| 25 |
### Model Sources
|
| 26 |
|
| 27 |
+
* **Repository:** [https://github.com/BarretBa/ICTHP](https://github.com/BarretBa/ICTHP)
|
| 28 |
+
* **Paper:** [Enhancing Reward Models for High-quality Image Generation: Beyond Text-Image Alignment](https://arxiv.org/abs/2507.19002)
|
| 29 |
+
* **Base Model:** CLIP-ViT-H-14 (Image Encoder + MLP Head)
|
| 30 |
+
* **Training Dataset:** [Pick-High datase](https://huggingface.co/datasets/8y/Pick-High-Dataset) and Pick-a-pic dataset (360,000 preference triplets)
|
| 31 |
|
| 32 |
## How to Get Started with the Model
|
| 33 |
|
|
|
|
| 108 |
primaryClass={cs.CV},
|
| 109 |
url={https://arxiv.org/abs/2507.19002},
|
| 110 |
}
|
| 111 |
+
```
|