add a training examples doc

examples/README.md

+## Training examples
+
+### Flowers DDPM 
+
+The command to train a DDPM UNet model on the Oxford Flowers dataset:
+
+```bash
+python -m torch.distributed.launch \
+  --nproc_per_node 4 \
+  train_ddpm.py \
+  --dataset="huggan/flowers-102-categories" \
+  --resolution=64 \
+  --output_path="flowers-ddpm" \
+  --batch_size=16 \
+  --num_epochs=100 \
+  --gradient_accumulation_steps=1 \
+  --lr=1e-4 \
+  --warmup_steps=500 \
+  --mixed_precision=no
+```
+
+A full ltraining run takes 2 hours on 4xV100 GPUs.
+
+<img src="https://user-images.githubusercontent.com/26864830/173855866-5628989f-856b-4725-a944-d6c09490b2df.png" width="500" />
+
+
+### Pokemon DDPM 
+
+The command to train a DDPM UNet model on the Pokemon dataset:
+
+```bash
+python -m torch.distributed.launch \
+  --nproc_per_node 4 \
+  train_ddpm.py \
+  --dataset="huggan/pokemon" \
+  --resolution=64 \
+  --output_path="flowers-ddpm" \
+  --batch_size=16 \
+  --num_epochs=100 \
+  --gradient_accumulation_steps=1 \
+  --lr=1e-4 \
+  --warmup_steps=500 \
+  --mixed_precision=no
+```
+
+A full ltraining run takes 2 hours on 4xV100 GPUs.
+
+<img src="https://user-images.githubusercontent.com/26864830/173856733-4f117f8c-97bd-4f51-8002-56b488c96df9.png" width="500" />