Update README.md

README.md

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 ---
 license: creativeml-openrail-m
+tags:
+- coreml
+- stable-diffusion
+- text-to-image
+- not_for_all_eyes
 ---
+# Core ML Converted Model:
+
+  - This model was converted to [Core ML for use on Apple Silicon devices](https://github.com/apple/ml-stable-diffusion). Conversion instructions can be found [here](https://github.com/godly-devotion/MochiDiffusion/wiki/How-to-convert-ckpt-or-safetensors-files-to-Core-ML).<br>
+  - Provide the model to an app such as Mochi Diffusion [Github](https://github.com/godly-devotion/MochiDiffusion) - [Discord](https://discord.gg/x2kartzxGv) to generate images.<br>
+  - `split_einsum` version is compatible with all compute unit options including Neural Engine.<br>
+  - `original` version is only compatible with CPU & GPU option.<br>
+  - Custom resolution versions are tagged accordingly.<br>
+  - `vae` tagged files have a vae embedded into the model.<br>
+  - Descriptions are posted as-is from original model source. Not all features and/or results may be available in CoreML format.<br>
+  - This model was converted with `vae-encoder` for i2i.
+  - Models that are 32 bit will have "fp32" in the filename.
+  
+# Note: Some models do not have the [unet split into chunks](https://github.com/apple/ml-stable-diffusion#-converting-models-to-core-ml).
+
+# RealBiter:
+Source(s): [CivitAI](https://civitai.com/models/16592/realbiter)
+
+This blend model aims to achieve versatility in generating images that are almost realistic but with a touch of fantasy and a polished aesthetic. It performs well with both illustrations and simulated photographs, but it particularly excels with the latter.
+
+It is recommended to use an appropriate VAE to avoid color gradients, and the vae-ft-mse-840000-ema-pruned model works especially well.
+
+The blend includes the Offset Noise model, which enhances contrasts and black processing. Incorporating an Offset Noise LORA in image generation can further enhance the results.
+
+The model is not specifically designed for NSFW content, but it easily generates this type of images.
+
+The model has been reviewed with CLIP tensors checker and it shows no deviation.