Update README.md

README.md

@@ -1,3 +1,68 @@
----
-license: apache-2.0
----
+---
+tags:
+- birder
+- pytorch
+license: apache-2.0
+---
+
+# Model Card for CLIP-based Aesthetic Predictor
+
+A simple MLP intended to run on CLIP embeddings to predict the "aesthetic quality" of an image (how much people like it on average).
+
+Trained by Christoph Schuhmann and adapted to suit the [Vision Data Curation](https://gitlab.com/birder/vision-data-curation) project.
+
+For more information see: <https://github.com/christophschuhmann/improved-aesthetic-predictor>
+
+## Model Details
+
+- **Model Type:** Aesthetic score regression model
+- **Input:** OpenAI CLIP embeddings ([vit_l14_pn_quick_gelu_openai-clip](https://huggingface.co/birder-project/vit_l14_pn_quick_gelu_openai-clip))
+- **Output:** A score between 0 and 10, where higher values correspond to more aesthetic images
+
+Original authorship: Adapted from Christoph Schuhmann's MLP Aesthetic Score Predictor
+
+## Model Usage
+
+This classifier operates on CLIP image embeddings rather than raw pixels. To run inference with the Birder framework:
+
+```sh
+# Download the CLIP backbone
+python -m birder.tools download-model vit_l14_pn_quick_gelu_openai-clip
+
+# Run prediction on a dataset
+python -m birder.scripts.predict \
+    -n vit_l14_pn_quick_gelu \
+    -t openai-clip \
+    --simple-crop \
+    --gpu \
+    --parallel \
+    --batch-size 256 \
+    --chunk-size 50000 \
+    --amp \
+    --amp-dtype bfloat16 \
+    --save-logits \
+    --suffix optional-dataset-name \
+    path/to/dataset
+
+# Can now run the aesthetic predictor on the saved logits
+```
+
+## Intended Use
+
+Primary use case: Ranking or filtering images by aesthetic appeal, dataset curation, and training data selection.
+
+Recommended scope: Research, dataset preparation, and large-scale data analysis.
+
+Not intended for: As a measure of artistic merit, cultural value, or taste preferences of specific individuals.
+
+## Citation
+
+```bibtex
+@misc{christophschuhmann2022improved-aesthetic-predictor,
+  author = {Christoph Schuhmann},
+  title = {MLP Aesthetic Score Predictor},
+  year = {2022},
+  url = {https://github.com/christophschuhmann/improved-aesthetic-predictor},
+  note = {Accessed: August 22, 2025},
+}
+```