Merge branch 'main' of https://huggingface.co/CompVis/stable-diffusion-v-1-1 into main

README.md

@@ -1,17 +1,20 @@
 ---
 license: other
+tags:
+- stable-diffusion
+- text-to-image
 ---
 
 # Stable Diffusion v1 Model Card
-This model card focuses on the model associated with the Stable Diffusion model, codebase available [here](https://github.com/CompVis/latent-diffusion).
+This model card focuses on the model associated with the Stable Diffusion model, available [here](https://github.com/CompVis/stable-diffusion).
 
 ## Model Details
-- **Developed by:** Robin Rombach, Patrick Esser, 
+- **Developed by:** Robin Rombach, Patrick Esser
 - **Model type:** Diffusion-based text-to-image generation model
 - **Language(s):** English
-- **License:** ~~Creative Commons 4.0~~
+- **License:** [Proprietary](LICENSE)
 - **Model Description:** This is a model that can be used to generate and modify images based on text prompts. It is a [Latent Diffusion Model](https://arxiv.org/abs/2112.10752) that uses a fixed, pretrained text encoder ([CLIP ViT-L/14](https://arxiv.org/abs/2103.00020)) as suggested in the [Imagen paper](https://arxiv.org/abs/2205.11487).
-- **Resources for more information:** [GitHub Repository](https://github.com/CompVis/latent-diffusion), [Paper](https://arxiv.org/abs/2112.10752).
+- **Resources for more information:** [GitHub Repository](https://github.com/CompVis/stable-diffusion), [Paper](https://arxiv.org/abs/2112.10752).
 - **Cite as:**
 
       @InProceedings{Rombach_2022_CVPR,
@@ -102,7 +105,7 @@ which were trained as follows,
   194k steps at resolution `512x512` on [laion-high-resolution](https://huggingface.co/datasets/laion/laion-high-resolution) (170M examples from LAION-5B with resolution `>= 1024x1024`).
 - `sd-v1-2.ckpt`: Resumed from `sd-v1-1.ckpt`.
   515k steps at resolution `512x512` on "laion-improved-aesthetics" (a subset of laion2B-en,
-filtered to images with an original size `>= 512x512`, estimated aesthetics score `> 5.0`, and an estimated watermark probability `< 0.5`. The watermark estimate is from the LAION-5B metadata, the aesthetics score is estimated using an improved aesthetics estimator, ~~that was trained on top of CLIP embeddings using the [Simulacra Aesthetic Captions](https://github.com/JD-P/simulacra-aesthetic-captions) dataset.~~).
+filtered to images with an original size `>= 512x512`, estimated aesthetics score `> 5.0`, and an estimated watermark probability `< 0.5`. The watermark estimate is from the LAION-5B metadata, the aesthetics score is estimated using an [improved aesthetics estimator](https://github.com/christophschuhmann/improved-aesthetic-predictor)).
 - `sd-v1-3.ckpt`: Resumed from `sd-v1-2.ckpt`. 195k steps at resolution `512x512` on "laion-improved-aesthetics" and 10\% dropping of the text-conditioning to improve [classifier-free guidance sampling](https://arxiv.org/abs/2207.12598).
 
 
@@ -117,7 +120,7 @@ Evaluations with different classifier-free guidance scales (1.5, 2.0, 3.0, 4.0,
 5.0, 6.0, 7.0, 8.0) and 50 PLMS sampling
 steps show the relative improvements of the checkpoints:
 
-![pareto](assets/v1-variants-scores.jpg) 
+![pareto](v1-variants-scores.jpg) 
 
 Evaluated using 50 PLMS steps and 10000 random prompts from the COCO2017 validation set, evaluated at 512x512 resolution.  Not optimized for FID scores.
 ## Environmental Impact
@@ -145,4 +148,4 @@ Based on that information, we estimate the following CO2 emissions using the [Ma
     }
 ```
 
-*This model card was written by: Robin Rombach and Patrick Esser and is based on the [DALL-E Mini model card](https://huggingface.co/dalle-mini/dalle-mini).*
+*This model card was written by: Robin Rombach and Patrick Esser and is based on the [DALL-E Mini model card](https://huggingface.co/dalle-mini/dalle-mini).*