Stable Diffusion Wip
The stable-diffusion-wip model has several potential use cases for a technical audience. One possible application is in image restoration, where damaged or degraded images can be inpainted to restore missing or corrupted parts. This could be useful in fields such as digital forensics or historical preservation. Another use case is in the entertainment industry, where this model could be used to enhance visual effects in movies or video games by seamlessly filling in gaps or removing unwanted objects from scenes. Additionally, this model could be integrated into photo editing software, allowing users to easily remove unwanted elements from their photographs or create composite images. The stable-diffusion-wip model has the potential to be the foundation for various products and practical uses. For example, it could power a user-friendly desktop application for inpainting that can be used by photographers, designers, or anyone needing to restore or edit images. It could also be integrated into cloud-based services that offer image restoration or enhancement capabilities. Furthermore, this model could serve as a basis for an API that developers can use to incorporate inpainting functionality into their own software applications or platforms. Overall, the stable-diffusion-wip model has the potential to revolutionize the field of inpainting and enable a wide range of practical applications.
- Cost per run
- Avg run time
- Nvidia A100 (40GB) GPU
|Llama 2 13b Embeddings||$?||172,645|
|Codellama 7b Instruct Gguf||$?||46|
|Llama 2 13b Chat Gguf||$?||1,352|
|Codellama 34b Instruct Gguf||$?||60|
You can use this area to play around with demo applications that incorporate the Stable Diffusion Wip model. These demos are maintained and hosted externally by third-party creators. If you see an error, message me on Twitter.
Currently, there are no demos available for this model.
Summary of this model and related resources.
|Model Name||Stable Diffusion Wip|
(development branch) Inpainting for Stable Diffusion
|Model Link||View on Replicate|
|API Spec||View on Replicate|
|Github Link||No Github link provided|
|Paper Link||No paper link provided|
How popular is this model, by number of runs? How popular is the creator, by the sum of all their runs?
How much does it cost to run this model? How long, on average, does it take to complete a run?
|Cost per Run||$0.0253|
|Prediction Hardware||Nvidia A100 (40GB) GPU|
|Average Completion Time||11 seconds|