update readme

README.md

@@ -7,6 +7,15 @@ This repository contains the model weights and configuration files for the [**Sp
 > [!Note]
 > These model weights have been **reproduced** with the released code and yield slightly different evaluation results compared to those reported in the original paper.
 
+## Model Card
+
+| dataset | :hugs: hf model repo | params |
+|:--:|:--:|:--:|
+| Animal-Faces | [`sphere-l-af`](sphere-l-af) | 642M |
+| Oxford-Flowers | [`sphere-l-of`](sphere-l-of) | 948M |
+| ImageNet | [`sphere-l-imagenet`](sphere-l-imagenet) | 950M |
+| ImageNet | [`sphere-xl-imagenet`](sphere-xl-imagenet) | 1.3B |
+
 Download model checkpoints and put them in `./workspace/experiments`.
 The directory tree should look like this:
 
@@ -19,3 +28,71 @@ The directory tree should look like this:
 |── sphere-l-imagenet
 |── sphere-xl-imagenet
 ```
+
+## Evaluation Results 
+
+Evaluate **ImageNet** models with `CFG = 1.4`:
+
+```bash
+# --job_dir can be
+#   sphere-l-imagenet, or sphere-xl-imagenet
+
+./run.sh eval.py \
+  --job_dir sphere-xl-imagenet \
+  --forward_steps 1 4 \
+  --report_fid rfid gfid \
+  --use_cfg True \
+  --cfg_min 1.4 \
+  --cfg_max 1.4 \
+  --cfg_position combo \
+  --rm_folder_after_eval True
+```
+
+The evaluation results will be saved in `./workspace/experiments/sphere-xl-imagenet/eval/`:
+
+| dataset | model | steps | rFID ↓ | gFID ↓ | IS ↑ |
+|:--:|:--|:--:|:--:|--:|:--:|
+ImageNet 256x256 | Sphere-L | 1 | 0.62 | 15.69 | 274.5 |
+|| Sphere-L | 4 | - | 4.78 | 259.1 |
+|| Sphere-XL | 1 | 0.62 | 14.52 | 299.3 |
+|| Sphere-XL | 4 | - | 4.05 | 266.0 |
+
+Evaluate unconditional **Animal-Faces** model:
+
+```bash
+./run.sh eval.py \
+  --job_dir sphere-l-af \
+  --forward_steps 1 4 \
+  --report_fid gfid \
+  --rm_folder_after_eval True
+```
+
+| dataset | model | steps | rFID ↓ | gFID ↓ | IS ↑ |
+|:--:|:--|:--:|:--:|:--:|:--:|
+Animal-Faces 256x256 | Sphere-L | 1 | - | 21.56 | 8.3 |
+|| Sphere-L | 4 | - | 18.73 | 9.8 |
+
+Evaluate **Oxford-Flowers** model with `CFG = 1.4`:
+
+```bash
+./run.sh eval.py \
+  --job_dir sphere-l-of \
+  --forward_steps 1 4 \
+  --report_fid gfid \
+  --use_cfg True \
+  --cfg_min 1.6 \
+  --cfg_max 1.6 \
+  --cfg_position combo \
+  --num_eval_samples 51000 \
+  --rm_folder_after_eval True \
+  --cache_sampling_noise False \
+```
+
+`--num_eval_samples = 51000` are set for 102 classes such that each class has 500 samples for evaluation on 8 gpus. 
+Adjust them accordingly if you have different number of gpus or want to evaluate on different number of samples.
+
+| dataset | model | steps | rFID ↓ | gFID ↓ | IS ↑ |
+|:--:|:--|:--:|:--:|:--:|:--:|
+| Oxford-Flowers 256x256 | Sphere-L | 1 | - | 25.10 | 3.4 |
+|| Sphere-L | 4 | - | 11.27 | 3.2 |
+