Improve model card: Add abstract, project page, update metadata (pipeline_tag, inference)

README.md

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 ---
-license: cc-by-nc-4.0
 base_model:
 - stabilityai/stable-diffusion-xl-base-1.0
-tags:
-- image-to-image
-inference: false
+license: cc-by-nc-4.0
+pipeline_tag: image-to-image
+inference: true
 ---
+
 # ✨ Latent Bridge Matching for Normals Estimation ✨
 
 Latent Bridge Matching (LBM) is a new, versatile and scalable method proposed in [LBM: Latent Bridge Matching for Fast Image-to-Image Translation](https://arxiv.org/abs/2503.07535) that relies on Bridge Matching in a latent space to achieve fast image-to-image translation.
 This model was trained to estimate the normal map from a given input image.
+
+Project page: https://gojasper.github.io/latent-bridge-matching/
 See also our [live demo](https://huggingface.co/spaces/jasperai/LBM_relighting) for image relighting and official [Github repo](https://github.com/gojasper/LBM).
 
+## Abstract
+In this paper, we introduce Latent Bridge Matching (LBM), a new, versatile and scalable method that relies on Bridge Matching in a latent space to achieve fast image-to-image translation. We show that the method can reach state-of-the-art results for various image-to-image tasks using only a single inference step. In addition to its efficiency, we also demonstrate the versatility of the method across different image translation tasks such as object removal, normal and depth estimation, and object relighting. We also derive a conditional framework of LBM and demonstrate its effectiveness by tackling the tasks of controllable image relighting and shadow generation.
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 ## How to use?
 To use this model you need first to install the associated `lbm` library by running the following
 ```bash