Update README.md

README.md

@@ -12,11 +12,11 @@ license: cc-by-nc-nd-4.0
 
 
 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.
+This model is a **108M** 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.
 
 
 <p align="center">
-   <img style="width:700px;" src="images/hf_grid.png">
+   <img style="width:700px;" src="images/flash_sdxl.jpg">
 </p>
 
 # How to use?
@@ -53,7 +53,7 @@ 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. 
+The model was trained for 20k iterations on 4 H100 GPUs (representing approximately a total of 176 GPU 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)