update model card (#6)

- update model card (26f5d7fc8ebd7f972e0cd0ebd589974867447e9a)


Co-authored-by: Kasiya <Kasiya13@users.noreply.huggingface.co>

README.md

@@ -18,28 +18,23 @@ pinned: true
 
 # About the model
 -----------------
-This model is a Stable Diffusion v1.5 fine-tune trained on the [Imaginary Network Expanded Dataset](https://github.com/Sygil-Dev/INE-dataset),
-you can browse the dataset better by using the [INE-dataset-explorer](https://huggingface.co/spaces/Sygil/INE-dataset-explorer) space. 
-It is an advanced version of Stable Diffusion and can generate nearly all kinds of images like humans, reflections, cities, architecture, fantasy, concepts arts, anime, manga, digital arts, landscapes, or nature views.
-This model allows the user to have total control of the generation as they can use multiple tags and namespaces to control almost everything
-on the final result including image composition.
-
-**Note that the prompt engineering techniques is a bit different from other models and Stable Diffusion,
-while you can still use normal prompts like in other Stable Diffusion models in order to get the best out of this model you will need to make use of tags and namespaces.
-More information about namespace will later be added.
-<!---
-[More about it here](promptingGuide.md)** \
--->
-\
-**If you find our work useful, please consider supporting us using one of the options below:**
-- [OpenCollective](https://opencollective.com/sygil_dev)
-
-**Join our Discord Server for supports and announcements**
-[![Join the Discord Server](https://badgen.net/discord/members/fTtcufxyHQ?icon=discord)](https://discord.gg/fTtcufxyHQ)
+This model is a fine-tune of Stable Diffusion v1.5, trained on the [Imaginary Network Expanded Dataset](https://github.com/Sygil-Dev/INE-dataset), with the big advantage of allowing the use of multiple namespaces (labeled tags) to control various parts of the final generation. 
+While current models usually are prone to “context errors” and need substantial negative prompting to set them on the right track, the use of namespaces in this model (eg. “species:seal” or “studio:dc”) stop the model from misinterpreting a seal as the singer Seal, or DC comics as Washington DC.
+
+As the model is fine-tuned on a wide variety of content, it’s able to generate many types of images and compositions, and easily outperforms the original model when it comes to portraits, architecture, reflections, fantasy, concept art, and landscapes without being hyper-specialized like other community fine-tunes that are currently available. 
+
+**Note: The prompt engineering techniques needed are slightly different from other fine-tunes and the original SD 1.5, so while you can still use your favorite prompts, for best results you might need to tweak them to make use of namespaces. A more detailed guide will be available shortly, but the examples here and this [Dataset Explorer](https://huggingface.co/spaces/Sygil/INE-dataset-explorer) should be able to start you off on the right track.
+
+If you find our work useful, please consider supporting us on [OpenCollective](https://opencollective.com/sygil_dev)! 
+
+This model is still in its infancy, so feel free to give us feedback on our [Discord Server](https://discord.gg/UjXFsf6mTu) or on the discussions section on huggingface. We plan to improve it with more, better tags in the future, so any help is always welcome 😛
+[![Join the Discord Server](https://badgen.net/discord/members/fTtcufxyHQ?icon=discord)](https://discord.gg/UjXFsf6mTu)
+
 
 # Showcase
 ![Showcase image](pictures/showcase-6.jpg)
 
+
 ## Examples
 
 Using the [🤗's Diffusers library](https://github.com/huggingface/diffusers) to run Sygil Diffusion in a simple and efficient manner.