Update README.md

README.md

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+---
 license: cc-by-nc-nd-4.0
 pipeline_tag: text-to-image
 widget:
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   - text: 'cinematic film still of Kodak Motion Picture Film: (Sharp Detailed Image) An Oscar winning movie for Best Cinematography a woman in a kimono standing on a subway train in Japan Kodak Motion Picture Film Style, shallow depth of field, vignette, highly detailed, high budget, bokeh, cinemascope, moody, epic, gorgeous, film grain, grainy'
     output:
       url: ComfyUI_00617_.png
-  - text: 'Super Closeup Portrait, action shot, Profoundly dark whiteish meadow, glass flowers, Stains, space grunge style, Jeanne d\'Arc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd'
+  - text: 'Super Closeup Portrait, action shot, Profoundly dark whiteish meadow, glass flowers, Stains, space grunge style, Jeanne d\Arc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd'
     output:
       url: ComfyUI_00615_.png
-  - text: 'Super Closeup Portrait, action shot, Profoundly dark whiteish meadow, glass flowers, Stains, space grunge style, Jeanne d\'Arc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd'
+  - text: 'Super Closeup Portrait, action shot, Profoundly dark whiteish meadow, glass flowers, Stains, space grunge style, Jeanne d\Arc wearing White Olive green used styled Cotton frock, Wielding thin silver sword, Sci-fi vibe, dirty, noisy, Vintage monk style, very detailed, hd'
     parameters:
       negative_prompt: >
         bad quality, bad anatomy, worst quality, low quality, low resolution,
@@ -28,6 +29,7 @@ widget:
         embedding:ac_neg1,
     output:
       url: ComfyUI_00614_.png
+---
 description: >
   This model is a fine-tuned version of Stable Diffusion 1.5, specifically enhanced for generating high-quality images of people, hands, and text. It has been trained on 131,000 high-quality, captioned image pairs generated using DALL-E 3. The training was conducted on four NVIDIA 3090 GPUs with NVLink over 16 hours, spanning 8 epochs.