feat: add support for SD2.x with TINY U-Nets (#939)

docs/distilled_sd.md

@@ -1,40 +1,66 @@
-# Running distilled models: SSD1B and SD1.x with tiny U-Nets
+# Running distilled models: SSD1B and SDx.x with tiny U-Nets
 
-## Preface
+## Preface 
 
-This kind of models have a reduced U-Net part. 
-Unlike other SDXL models the U-Net of SSD1B has only one middle block and lesser attention layers in up and down blocks, resulting in relatively smaller files. Running these models saves more than 33% of the time. For more details, refer to Segmind's paper on https://arxiv.org/abs/2401.02677v1 .
-Unlike other SD 1.x models Tiny-UNet models consist of only 6 U-Net blocks, resulting in relatively smaller files (approximately 1 GB). Running these models saves almost 50% of the time. For more details, refer to the paper: https://arxiv.org/pdf/2305.15798.pdf .
+These models feature a reduced U-Net architecture. Unlike standard SDXL models, the SSD-1B U-Net contains only one middle block and fewer attention layers in its up- and down-blocks, resulting in significantly smaller file sizes. Using these models can reduce inference time by more than 33%. For more details, refer to Segmind's paper: https://arxiv.org/abs/2401.02677v1.
+Similarly, SD1.x- and SD2.x-style models with a tiny U-Net consist of only 6 U-Net blocks, leading to very small files and time savings of up to 50%. For more information, see the paper: https://arxiv.org/pdf/2305.15798.pdf.
 
 ## SSD1B
 
-Unfortunately not all of this models follow the standard model parameter naming mapping. 
-Anyway there are some very useful SSD1B models available online, such as:
+Note that not all of these models follow the standard parameter naming conventions. However, several useful SSD-1B models are available online, such as:
 
  * https://huggingface.co/segmind/SSD-1B/resolve/main/SSD-1B-A1111.safetensors
- * https://huggingface.co/hassenhamdi/SSD-1B-fp8_e4m3fn/resolve/main/SSD-1B_fp8_e4m3fn.safetensors 
+ * https://huggingface.co/hassenhamdi/SSD-1B-fp8_e4m3fn/resolve/main/SSD-1B_fp8_e4m3fn.safetensors
 
-Also there are useful LORAs available:
+Useful LoRAs are also available:
 
  * https://huggingface.co/seungminh/lora-swarovski-SSD-1B/resolve/main/pytorch_lora_weights.safetensors
- * https://huggingface.co/kylielee505/mylcmlorassd/resolve/main/pytorch_lora_weights.safetensors   
+ * https://huggingface.co/kylielee505/mylcmlorassd/resolve/main/pytorch_lora_weights.safetensors
 
-You can use this files **out-of-the-box** - unlike models in next section.
+These files can be used out-of-the-box, unlike the models described in the next section.
 
 
-## SD1.x with tiny U-Nets
+## SD1.x, SD2.x with tiny U-Nets
 
-There are some Tiny SD 1.x models available online, such as:
+These models require conversion before use. You will need a Python script provided by the diffusers team, available on GitHub:
+
+ * https://raw.githubusercontent.com/huggingface/diffusers/refs/heads/main/scripts/convert_diffusers_to_original_stable_diffusion.py
+
+### SD2.x
+
+NotaAI provides the following model online:
+
+* https://huggingface.co/nota-ai/bk-sdm-v2-tiny
+
+Creating a .safetensors file involves two steps. First, run this short Python script to download the model from Hugging Face:
+
+```python
+from diffusers import StableDiffusionPipeline
+pipe = StableDiffusionPipeline.from_pretrained("nota-ai/bk-sdm-v2-tiny",cache_dir="./")
+```
+
+Second, create the .safetensors file by running:
+
+```bash
+python convert_diffusers_to_original_stable_diffusion.py \
+      --model_path  models--nota-ai--bk-sdm-v2-tiny/snapshots/68277af553777858cd47e133f92e4db47321bc74 \
+      --checkpoint_path bk-sdm-v2-tiny.safetensors --half --use_safetensors
+```
+
+This will generate the **file bk-sdm-v2-tiny.safetensors**, which is now ready for use with sd.cpp.
+
+### SD1.x
+
+Several Tiny SD 1.x models are available online, such as:
 
  * https://huggingface.co/segmind/tiny-sd
  * https://huggingface.co/segmind/portrait-finetuned
  * https://huggingface.co/nota-ai/bk-sdm-tiny
 
-These models need some conversion, for example because partially tensors are **non contiguous** stored. To create a usable checkpoint file, follow these **easy** steps:
+These models also require conversion, partly because some tensors are stored in a non-contiguous manner. To create a usable checkpoint file, follow these simple steps:
+Download and prepare the model using Python: 
 
-### Download model from Hugging Face
-
-Download the model using Python on your computer, for example this way:
+##### Download the model using Python on your computer, for example this way:
 
 ```python
 import torch
@@ -46,35 +72,22 @@ for param in unet.parameters():
 pipe.save_pretrained("segmindtiny-sd", safe_serialization=True)
 ```
 
-### Convert that to a ckpt file 
-
-To convert the downloaded model to a checkpoint file, you need another Python script. Download the conversion script from here:
-
- * https://raw.githubusercontent.com/huggingface/diffusers/refs/heads/main/scripts/convert_diffusers_to_original_stable_diffusion.py
-
-
-### Run convert script
-
-Now, run that conversion script:
+##### Run the conversion script:
 
 ```bash
 python convert_diffusers_to_original_stable_diffusion.py \
-	--model_path  ./segmindtiny-sd \
-	--checkpoint_path ./segmind_tiny-sd.ckpt --half
+      --model_path  ./segmindtiny-sd \
+      --checkpoint_path ./segmind_tiny-sd.ckpt --half
 ```
 
-The file **segmind_tiny-sd.ckpt**  will be generated and is now ready to use with sd.cpp
-
-You can follow a similar process for other models mentioned above from Hugging Face. 
+The file segmind_tiny-sd.ckpt will be generated and is now ready for use with sd.cpp. You can follow a similar process for the other models mentioned above.
 
 
-### Another ckpt file on the net
-
-There is another model file available online: 
+### Another available .ckpt file:
 
  * https://huggingface.co/ClashSAN/small-sd/resolve/main/tinySDdistilled.ckpt
- 
-If you want to use that, you have to adjust some **non-contiguous tensors** first:
+
+To use this file, you must first adjust its non-contiguous tensors:
 
 ```python
 import torch