![CLIP Text Embeddings. This plot shows a TSNE of CLIP's pooled output... | Download Scientific Diagram CLIP Text Embeddings. This plot shows a TSNE of CLIP's pooled output... | Download Scientific Diagram](https://www.researchgate.net/publication/364471045/figure/fig6/AS:11431281091080291@1666301248003/CLIP-Text-Embeddings-This-plot-shows-a-TSNE-of-CLIPs-pooled-output-for-the-same.png)
CLIP Text Embeddings. This plot shows a TSNE of CLIP's pooled output... | Download Scientific Diagram
![AK on X: "Visualization of reconstructions of CLIP latents from progressively more PCA dimensions (20, 30, 40, 80, 120, 160, 200, 320 dimensions), with the original source image on the far right. AK on X: "Visualization of reconstructions of CLIP latents from progressively more PCA dimensions (20, 30, 40, 80, 120, 160, 200, 320 dimensions), with the original source image on the far right.](https://pbs.twimg.com/media/FPq8WriWUAM_N27.jpg:large)
AK on X: "Visualization of reconstructions of CLIP latents from progressively more PCA dimensions (20, 30, 40, 80, 120, 160, 200, 320 dimensions), with the original source image on the far right.
![MosaicML, now part of Databricks! on X: "[4/8] Speedup 2: Precomputing Latents. The VAE image encoder and CLIP text encoder are pre-trained and frozen when training SD2. That means we can pre-compute MosaicML, now part of Databricks! on X: "[4/8] Speedup 2: Precomputing Latents. The VAE image encoder and CLIP text encoder are pre-trained and frozen when training SD2. That means we can pre-compute](https://pbs.twimg.com/media/Fu0UET1aUAYD7xI.jpg:large)
MosaicML, now part of Databricks! on X: "[4/8] Speedup 2: Precomputing Latents. The VAE image encoder and CLIP text encoder are pre-trained and frozen when training SD2. That means we can pre-compute
![OpenAI's unCLIP Text-to-Image System Leverages Contrastive and Diffusion Models to Achieve SOTA Performance | Synced OpenAI's unCLIP Text-to-Image System Leverages Contrastive and Diffusion Models to Achieve SOTA Performance | Synced](https://i0.wp.com/syncedreview.com/wp-content/uploads/2022/04/image-45.png?resize=886%2C432&ssl=1)
OpenAI's unCLIP Text-to-Image System Leverages Contrastive and Diffusion Models to Achieve SOTA Performance | Synced
![Left) Overview of our proposed CLIP-guided latent optimization to find... | Download Scientific Diagram Left) Overview of our proposed CLIP-guided latent optimization to find... | Download Scientific Diagram](https://www.researchgate.net/publication/359311018/figure/fig1/AS:1134854779486208@1647581872043/Left-Overview-of-our-proposed-CLIP-guided-latent-optimization-to-find-the-reference_Q320.jpg)