Glid 3 Xl
The glid-3-xl model has several potential use cases. One possible application is in computer vision research, where it can be used to generate images based on textual descriptions. This could be particularly useful in tasks such as image synthesis or data augmentation for training deep learning models. Additionally, the model's fine-tuning for inpainting makes it suitable for applications in image restoration or completion. It can be employed to fill in missing or damaged parts of images, potentially helping in tasks like digital restoration, artistic rendering, or virtual environment generation. Considering its capabilities and performance, potential products or practical uses that could be derived from this model include smart image editing software, virtual reality content creation tools, or even AI-powered art assistants that can turn textual descriptions into realistic visual representations.
- Cost per run
- Avg run time
- Nvidia T4 GPU
|Mannequin Gan 3 Electric Boogaloo 2||$?||850|
|Clip Guided Diffusion||$?||40,435|
You can use this area to play around with demo applications that incorporate the Glid 3 Xl 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||Glid 3 Xl|
CompVis `latent-diffusion text2im` finetuned for inpainting.
|Model Link||View on Replicate|
|API Spec||View on Replicate|
|Github Link||View on Github|
|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||$0.011|
|Prediction Hardware||Nvidia T4 GPU|
|Average Completion Time||20 seconds|