Update README.md

- Added metrics (Table 3 from the paper), and some training details
- Added Eyal's name

README.md

@@ -11,7 +11,7 @@ license: cc-by-nc-nd-4.0
 # ⚡ FlashDiffusion: FlashSDXL ⚡
 
 
-Flash Diffusion is a diffusion distillation method proposed in [ADD ARXIV]() *by Clément Chadebec, Onur Tasar and Benjamin Aubin.*
+Flash Diffusion is a diffusion distillation method proposed in [ADD ARXIV]() *by Clément Chadebec, Onur Tasar, Eyal Benaroche, and Benjamin Aubin.*
 This model is a **26.4M** LoRA distilled version of [SDXL](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0) model that is able to generate images in **4 steps**. The main purpose of this model is to reproduce the main results of the paper.
 
 
@@ -26,7 +26,7 @@ The model can be used using the `StableDiffusionPipeline` from `diffusers` libra
 ```python
 from diffusers import DiffusionPipeline, LCMScheduler
 
-adapter_id = "jasperai/flash-sd"
+adapter_id = "jasperai/flash-sdxl"
 
 pipe = DiffusionPipeline.from_pretrained(
   "stabilityai/stable-diffusion-xl-base-1.0",
@@ -53,7 +53,11 @@ image = pipe(prompt, num_inference_steps=4, guidance_scale=0).images[0]
 </p>
 
 # Training Details
+The model was trained for 20k iterations on 4 H100 GPUs (representing approximately 176 hours of training). Please refer to the [paper]() for further parameters details. 
 
-
+**Metrics on COCO 2014 validation (Table 3)**
+  - FID-10k: 21.62 (4 NFE)
+  - CLIP Score: 0.327 (4 NFE)
+   
 ## License
 This model is released under the the Creative Commons BY-NC license.