Update README.md

README.md

@@ -1,3 +1,66 @@
----
-license: creativeml-openrail-m
----
+---
+license: creativeml-openrail-m
+library_name: diffusers
+pipeline_tag: text-to-image
+base_model: stabilityai/stable-diffusion-xl-base-1.0
+tags:
+- safetensors
+- stable-diffusion
+- lora
+- template:sd-lora
+- sdxl
+- flash
+- sdxl-flash
+- lightning
+- turbo
+- lcm
+- hyper
+- fast
+- fast-sdxl
+- sd-community
+instance_prompt: <lora:sdxl-flash-lora:0.55>
+inference:
+  parameters:
+    num_inference_steps: 7
+    guidance_scale: 3
+    negative_prompt: >-
+      (deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong
+      anatomy, extra limb, missing limb, floating limbs, (mutated hands and
+      fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting,
+      blurry, amputation
+---
+# **SDXL Flash** *in collaboration with [Project Fluently](https://hf.co/fluently)*
+
+![preview](images/preview.png)
+
+Introducing the new fast model SDXL Flash, we learned that all fast XL models work fast, but the quality decreases, and we also made a fast model, but it is not as fast as LCM, Turbo, Lightning and Hyper, but the quality is higher. Below you will see the study with steps and cfg.
+
+### **Work with LoRA**
+
+Trigger word: ```<lora:sdxl-flash-lora:0.55>```
+
+### Steps and CFG (Guidance)
+
+![steps_and_cfg_grid_test](images/steps_cfg_grid.png)
+
+### Optimal settings
+- **Steps**: 6-9
+- **CFG Scale**: 2.5-3.5
+- **Sampler**: DPM++ SDE
+
+### Diffusers usage
+
+```bash
+pip install torch diffusers
+```
+
+```py
+import torch
+from diffusers import StableDiffusionXLPipeline, DPMSolverSinglestepScheduler
+# Load model.
+pipe = StableDiffusionXLPipeline.from_pretrained("sd-community/sdxl-flash", torch_dtype=torch.float16).to("cuda")
+# Ensure sampler uses "trailing" timesteps.
+pipe.scheduler = DPMSolverSinglestepScheduler.from_config(pipe.scheduler.config, timestep_spacing="trailing")
+# Image generation.
+pipe("a happy dog, sunny day, realism", num_inference_steps=7, guidance_scale=3).images[0].save("output.png")
+```