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. |