diff --git a/README.md b/README.md
index 0c6783a..1ed914f 100644
--- a/README.md
+++ b/README.md
@@ -60,68 +60,122 @@ pytest
 
 ### Hello World
 
-Here is how to perform a text-to-image inference using the Stable Diffusion 1.5 foundational model patched with a Pokemon LoRA:
+Goal: turn Refiners' mascot into a [Dragon Quest Slime](https://en.wikipedia.org/wiki/Slime_(Dragon_Quest)) plush in a one-shot manner thanks to a powerful combo of adapters:
+- IP-Adapter: to capture the Slime plush visual appearance into an image prompt (no prompt engineering needed)
+- T2I-Adapter: to guide the generation with the mascot's geometry
+- Self-Attention-Guidance (SAG): to increase the sharpness
 
-Step 1: prepare the model weights in refiners' format:
+![hello world overview](https://raw.githubusercontent.com/finegrain-ai/refiners/main/assets/hello_world_overview.png)
+
+**Step 1**: convert SDXL weights to the Refiners' format:
 
 ```bash
-python scripts/conversion/convert_transformers_clip_text_model.py --to clip.safetensors
-python scripts/conversion/convert_diffusers_autoencoder_kl.py --to lda.safetensors
-python scripts/conversion/convert_diffusers_unet.py --to unet.safetensors
+python scripts/conversion/convert_transformers_clip_text_model.py --from "stabilityai/stable-diffusion-xl-base-1.0" --subfolder2 text_encoder_2 --to clip_text_xl.safetensors --half
+python scripts/conversion/convert_diffusers_unet.py --from "stabilityai/stable-diffusion-xl-base-1.0" --to unet_xl.safetensors --half
+python scripts/conversion/convert_diffusers_autoencoder_kl.py --from "madebyollin/sdxl-vae-fp16-fix" --subfolder "" --to lda_xl.safetensors --half
 ```
 
-> Note: this will download the original weights from https://huggingface.co/runwayml/stable-diffusion-v1-5 which takes some time. If you already have this repo cloned locally, use the `--from /path/to/stable-diffusion-v1-5` option instead.
+> Note: this will download the original weights from https://huggingface.co/ which takes some time. If you already have this repo cloned locally, use the `--from /path/to/stabilityai/stable-diffusion-xl-base-1.0` option instead.
 
-Step 2: download and convert a community Pokemon LoRA, e.g. [this one](https://huggingface.co/pcuenq/pokemon-lora)
+And then convert IP-Adapter and T2I-Adapter weights (note: SAG is parameter-free):
 
 ```bash
-curl -LO https://huggingface.co/pcuenq/pokemon-lora/resolve/main/pytorch_lora_weights.bin
-python scripts/conversion/convert_diffusers_lora.py \
-  --from pytorch_lora_weights.bin \
-  --to pokemon_lora.safetensors
+python scripts/conversion/convert_diffusers_t2i_adapter.py --from "TencentARC/t2i-adapter-canny-sdxl-1.0" --to t2i_canny_xl.safetensors --half
+python scripts/conversion/convert_transformers_clip_image_model.py --from "stabilityai/stable-diffusion-2-1-unclip" --to clip_image.safetensors --half
+curl -LO https://huggingface.co/h94/IP-Adapter/resolve/main/sdxl_models/ip-adapter_sdxl_vit-h.bin
+python scripts/conversion/convert_diffusers_ip_adapter.py --from ip-adapter_sdxl_vit-h.bin --half
 ```
 
-Step 3: run inference using the GPU:
+**Step 2**: download input images:
+
+```bash
+curl -O https://raw.githubusercontent.com/finegrain-ai/refiners/main/assets/dropy_logo.png
+curl -O https://raw.githubusercontent.com/finegrain-ai/refiners/main/assets/dropy_canny.png
+curl -O https://raw.githubusercontent.com/finegrain-ai/refiners/main/assets/dragon_quest_slime.jpg
+```
+
+**Step 3**: generate an image using the GPU:
 
 ```python
-from refiners.foundationals.latent_diffusion import StableDiffusion_1
-from refiners.foundationals.latent_diffusion.lora import SD1LoraAdapter
-from refiners.fluxion.utils import load_from_safetensors, manual_seed
 import torch
 
+from PIL import Image
 
-sd15 = StableDiffusion_1(device="cuda")
-sd15.clip_text_encoder.load_from_safetensors("clip.safetensors")
-sd15.lda.load_from_safetensors("lda.safetensors")
-sd15.unet.load_from_safetensors("unet.safetensors")
+from refiners.foundationals.latent_diffusion.stable_diffusion_xl import StableDiffusion_XL
+from refiners.foundationals.latent_diffusion import SDXLIPAdapter, SDXLT2IAdapter
+from refiners.fluxion.utils import manual_seed, image_to_tensor, load_from_safetensors
 
-SD1LoraAdapter.from_safetensors(target=sd15, checkpoint_path="pokemon_lora.safetensors", scale=1.0).inject()
+# Load inputs
+init_image = Image.open("dropy_logo.png")
+image_prompt = Image.open("dragon_quest_slime.jpg")
+condition_image = Image.open("dropy_canny.png")
 
-prompt = "a cute cat"
+# Load SDXL
+sdxl = StableDiffusion_XL(device="cuda", dtype=torch.float16)
+sdxl.clip_text_encoder.load_from_safetensors("clip_text_xl.safetensors")
+sdxl.lda.load_from_safetensors("lda_xl.safetensors")
+sdxl.unet.load_from_safetensors("unet_xl.safetensors")
+
+# Load and inject adapters
+ip_adapter = SDXLIPAdapter(target=sdxl.unet, weights=load_from_safetensors("ip-adapter_sdxl_vit-h.safetensors"))
+ip_adapter.clip_image_encoder.load_from_safetensors("clip_image.safetensors")
+ip_adapter.inject()
+
+t2i_adapter = SDXLT2IAdapter(
+    target=sdxl.unet, name="canny", weights=load_from_safetensors("t2i_canny_xl.safetensors")
+).inject()
+
+# Tune parameters
+seed = 9752
+first_step = 1
+ip_adapter.set_scale(0.85)
+t2i_adapter.set_scale(0.8)
+sdxl.set_num_inference_steps(50)
+sdxl.set_self_attention_guidance(enable=True, scale=0.75)
 
 with torch.no_grad():
-    clip_text_embedding = sd15.compute_clip_text_embedding(prompt)
+    # Note: default text prompts for IP-Adapter
+    clip_text_embedding, pooled_text_embedding = sdxl.compute_clip_text_embedding(
+        text="best quality, high quality", negative_text="monochrome, lowres, bad anatomy, worst quality, low quality"
+    )
+    clip_image_embedding = ip_adapter.compute_clip_image_embedding(ip_adapter.preprocess_image(image_prompt))
 
-sd15.set_num_inference_steps(30)
+    negative_text_embedding, conditional_text_embedding = clip_text_embedding.chunk(2)
+    negative_image_embedding, conditional_image_embedding = clip_image_embedding.chunk(2)
 
-manual_seed(2)
-x = torch.randn(1, 4, 64, 64, device=sd15.device)
+    clip_text_embedding = torch.cat(
+        (
+            torch.cat([negative_text_embedding, negative_image_embedding], dim=1),
+            torch.cat([conditional_text_embedding, conditional_image_embedding], dim=1),
+        )
+    )
+    time_ids = sdxl.default_time_ids
 
-with torch.no_grad():
-    for step in sd15.steps:
-        x = sd15(
+    condition = image_to_tensor(condition_image.convert("RGB"), device=sdxl.device, dtype=sdxl.dtype)
+    t2i_adapter.set_condition_features(features=t2i_adapter.compute_condition_features(condition))
+
+    manual_seed(seed=seed)
+    x = sdxl.init_latents(size=(1024, 1024), init_image=init_image, first_step=first_step).to(
+        device=sdxl.device, dtype=sdxl.dtype
+    )
+
+    for step in sdxl.steps[first_step:]:
+        x = sdxl(
             x,
             step=step,
             clip_text_embedding=clip_text_embedding,
-            condition_scale=7.5,
+            pooled_text_embedding=pooled_text_embedding,
+            time_ids=time_ids,
         )
-    predicted_image = sd15.lda.decode_latents(x)
-    predicted_image.save("pokemon_cat.png")
+    predicted_image = sdxl.lda.decode_latents(x=x)
+
+predicted_image.save("output.png")
+print("done: see output.png")
 ```
 
 You should get:
 
-![pokemon cat output](https://raw.githubusercontent.com/finegrain-ai/refiners/main/assets/pokemon_cat.png)
+![dropy slime output](https://raw.githubusercontent.com/finegrain-ai/refiners/main/assets/dropy_slime_9752.png)
 
 ### Training
 
diff --git a/assets/README.md b/assets/README.md
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+# Note about this data
+
+- `dragon_quest_slime.jpg`: from [My Dragon Quest Slime Plush Collection ](https://www.reddit.com/r/dragonquest/comments/x2q2y3/my_dragon_quest_slime_plush_collection/) by [RetroGamer489](https://www.reddit.com/user/RetroGamer489/)
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