thanks to SimianLuo ❤

.gitattributes

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+image.png filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,74 @@
+---
+library_name: diffusers
+base_model: stabilityai/stable-diffusion-xl-base-1.0
+tags:
+- text-to-image
+license: openrail++
+inference: false
+---
+
+# Latent Consistency Model (LCM): SDXL
+
+Latent Consistency Model (LCM) was proposed in [Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference](https://arxiv.org/abs/2310.04378) 
+by *Simian Luo, Yiqin Tan et al.* and [Simian Luo](https://huggingface.co/SimianLuo), [Suraj Patil](https://huggingface.co/valhalla), and [Daniel Gu](https://huggingface.co/dg845)
+succesfully applied the same approach to create LCM for SDXL.
+
+This checkpoint is a LCM distilled version of [`stable-diffusion-xl-base-1.0`](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0) that allows
+to reduce the number of inference steps to only between **2 - 8 steps**.
+
+
+## Usage
+
+LCM SDXL is supported in 🤗 Hugging Face Diffusers library from version v0.23.0 onwards. To run the model, first 
+install the latest version of the Diffusers library as well as `peft`, `accelerate` and `transformers`.
+audio dataset from the Hugging Face Hub:
+
+```bash
+pip install --upgrade pip
+pip install --upgrade diffusers transformers accelerate peft
+```
+
+### Text-to-Image
+
+The model can be loaded with it's base pipeline `stabilityai/stable-diffusion-xl-base-1.0`. Next, the scheduler needs to be changed to [`LCMScheduler`](https://huggingface.co/docs/diffusers/v0.22.3/en/api/schedulers/lcm#diffusers.LCMScheduler) and we can reduce the number of inference steps to just 2 to 8 steps.
+Please make sure to either disable `guidance_scale` or use values between 1.0 and 2.0.
+
+```python
+from diffusers import UNet2DConditionModel, DiffusionPipeline, LCMScheduler
+
+unet = UNet2DConditionModel.from_pretrained("latent-consistency/lcm-sdxl", torch_dtype=torch.float16, variant="fp16")
+pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", unet=unet, torch_dtype=torch.float16, variant="fp16")
+
+pipe.scheduler = LCMScheduler.from_config(sd_pipe.scheduler.config)
+pipe.to("cuda")
+
+prompt = "a close-up picture of an old man standing in the rain"
+
+image = pipe(prompt, num_inference_steps=4, guidance_scale=8.0).images[0]
+```
+
+![](./image.png)
+
+### Image-to-Image
+
+Works as well! TODO docs
+
+### Inpainting
+
+Works as well! TODO docs
+
+### ControlNet
+
+Works as well! TODO docs
+
+### T2I Adapter
+
+Works as well! TODO docs
+
+## Speed Benchmark
+
+TODO
+
+## Training
+
+TODO

config.json

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+{
+ "_class_name": "UNet2DConditionModel",
+ "_diffusers_version": "0.23.0.dev0",
+ "_name_or_path": "/home/patrick/lcm-sdxl-base-1.0",
+ "act_fn": "silu",
+ "addition_embed_type": "text_time",
+ "addition_embed_type_num_heads": 64,
+ "addition_time_embed_dim": 256,
+ "attention_head_dim": [
+ 5,
+ 10,
+ 20
+ ],
+ "attention_type": "default",
+ "block_out_channels": [
+ 320,
+ 640,
+ 1280
+ ],
+ "center_input_sample": false,
+ "class_embed_type": null,
+ "class_embeddings_concat": false,
+ "conv_in_kernel": 3,
+ "conv_out_kernel": 3,
+ "cross_attention_dim": 2048,
+ "cross_attention_norm": null,
+ "down_block_types": [
+ "DownBlock2D",
+ "CrossAttnDownBlock2D",
+ "CrossAttnDownBlock2D"
+ ],
+ "downsample_padding": 1,
+ "dropout": 0.0,
+ "dual_cross_attention": false,
+ "encoder_hid_dim": null,
+ "encoder_hid_dim_type": null,
+ "flip_sin_to_cos": true,
+ "freq_shift": 0,
+ "in_channels": 4,
+ "layers_per_block": 2,
+ "mid_block_only_cross_attention": null,
+ "mid_block_scale_factor": 1,
+ "mid_block_type": "UNetMidBlock2DCrossAttn",
+ "norm_eps": 1e-05,
+ "norm_num_groups": 32,
+ "num_attention_heads": null,
+ "num_class_embeds": null,
+ "only_cross_attention": false,
+ "out_channels": 4,
+ "projection_class_embeddings_input_dim": 2816,
+ "resnet_out_scale_factor": 1.0,
+ "resnet_skip_time_act": false,
+ "resnet_time_scale_shift": "default",
+ "reverse_transformer_layers_per_block": null,
+ "sample_size": 128,
+ "time_cond_proj_dim": 256,
+ "time_embedding_act_fn": null,
+ "time_embedding_dim": null,
+ "time_embedding_type": "positional",
+ "timestep_post_act": null,
+ "transformer_layers_per_block": [
+ 1,
+ 2,
+ 10
+ ],
+ "up_block_types": [
+ "CrossAttnUpBlock2D",
+ "CrossAttnUpBlock2D",
+ "UpBlock2D"
+ ],
+ "upcast_attention": null,
+ "use_linear_projection": true
+}

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