Update README.md

README.md

@@ -26,6 +26,42 @@ ConditioningCombine nodes *should* work for combining multiple labels. The area
 
 ![DIT_WORKFLOW_IMG](https://github.com/city96/ComfyUI_ExtraModels/assets/125218114/cdd4ec94-b0eb-436a-bf23-a3bcef8d7b90)
 
+## T5
+### Model
+
+The model files can be downloaded from the [DeepFloyd/t5-v1_1-xxl](https://huggingface.co/DeepFloyd/t5-v1_1-xxl/tree/main) repository.
+
+You will need to download the following 4 files:
+ - `config.json`
+ - `pytorch_model-00001-of-00002.bin`
+ - `pytorch_model-00002-of-00002.bin`
+ - `pytorch_model.bin.index.json`
+
+Place them in your `ComfyUI/models/t5` folder. You can put them in a subfolder called "t5-v1.1-xxl" though it doesn't matter. There are int8 safetensor files in the other DeepFloyd repo, thought they didn't work for me.
+
+### Usage
+
+Loaded onto the CPU, it'll use about 22GBs of system RAM. Depending on which weights you use, it might use slightly more during loading.
+
+Loaded in bnb4bit mode, it only takes around 6GB VRAM, making it work with 12GB cards. The only drawback is that it'll constantly stay in VRAM since BitsAndBytes doesn't allow moving the weights to the system RAM temporarily. Switching to a different workflow *should* still release the VRAM as expected. Pascal cards (1080ti, P40) seem to struggle with 4bit. Select "cpu" if you encounter issues.
+
+On windows, you may need a newer version of bitsandbytes for 4bit. Try `python -m pip install bitsandbytes --prefer-binary --extra-index-url=https://jllllll.github.io/bitsandbytes-windows-webui`
+
+You may also need to upgrade transformers. `pip install --upgrade transformers`
+
+## PixArt
+
+This is mostly a proof of concept, as the model weights have not been released officially. [Sample workflow here](https://github.com/city96/ComfyUI_ExtraModels/files/13192747/PixArt.json)
+
+Make sure to `pip install timm==0.6.13`. xformers is optional but strongly recommended as torch SDP is only partially implemented, if that.
+
+Limitations:
+- The default `KSampler` uses a different noise schedule/sampling algo (I think), so it most likely won't work as expected.
+- `PixArt DPM Sampler` requires the negative prompt to be shorter than the positive prompt.
+- `PixArt DPM Sampler` can only work with a batch size of 1.
+- `PixArt T5 Text Encode` is from the reference implementation, therefore it doesn't support weights. `T5 Text Encode` support weights, but I can't attest to the correctness of the implementation.
+
+
 ## VAE
 
 A few custom VAE models are supported. The option to select a different dtype when loading is also possible, which can be useful for testing/comparisons.