Update README.md

README.md

@@ -2,6 +2,9 @@
 license: apache-2.0
 paper: https://arxiv.org/abs/2510.12670
 homepage: https://github.com/IBM/TerraCodec
+datasets:
+- embed2scale/SSL4EO-S12-v1.1
+library_name: terratorch
 ---
 
 # TerraCodec
@@ -24,10 +27,10 @@ Compared to classical codecs such as JPEG2000 or WebP, TerraCodec achieves **3
 
 | Model | Available Checkpoints | Description |
 |---|---|---|
-| `terracodec_v1_fp_s2l2a` | λ = 0.5, 2, 10, 40, 200 | Factorized-prior image codec. Smallest model and strong baseline for multispectral image compression. |
-| `terracodec_v1_elic_s2l2a` | λ = 0.5, 2, 10, 40, 200 | Enhanced entropy model with spatial and channel context for improved rate–distortion performance. |
-| `terracodec_v1_tt_s2l2a` | λ = 0.4, 1, 5, 20, 100, 200, 700 | Temporal Transformer codec modeling redundancy across seasonal image sequences. |
-| `flextec_v1_s2l2a` | **Single checkpoint** (quality = 1–16) | Flexible-rate temporal codec. One model supports multiple compression levels via token-based quality settings. |
+| [`terracodec_v1_fp_s2l2a`](https://huggingface.co/embed2scale/TerraCodec-1.0-ELIC-S2L2A) | λ = 0.5, 2, 10, 40, 200 | Factorized-prior image codec. Smallest model and strong baseline for multispectral image compression. |
+| [`terracodec_v1_elic_s2l2a`](https://huggingface.co/embed2scale/TerraCodec-1.0-FP-S2L2A) | λ = 0.5, 2, 10, 40, 200 | Enhanced entropy model with spatial and channel context for improved rate–distortion performance. |
+| [`terracodec_v1_tt_s2l2a`](https://huggingface.co/embed2scale/TerraCodec-1.0-TT-S2L2A) | λ = 0.4, 1, 5, 20, 100, 200, 700 | Temporal Transformer codec modeling redundancy across seasonal image sequences. |
+| [`flextec_v1_s2l2a`](https://huggingface.co/embed2scale/TerraCodec-1.0-FlexTEC-S2L2A) | **Single checkpoint** (quality = 1–16) | Flexible-rate temporal codec. One model supports multiple compression levels via token-based quality settings. |
 
 Lower λ / quality → **higher compression**  
 Higher λ / quality → **higher reconstruction quality**
@@ -43,7 +46,7 @@ This repository contains the **TEC-FP (Factorized Prior)** variants of TerraCode
 TEC-FP is a convolutional encoder–decoder neural compression model with a fully factorized entropy model for the latent representation. Each quantized latent variable is modeled independently without spatial or channel context.
 This design enables efficient parallel entropy coding. TEC-FP is the smallest and fastest image codec in the TerraCodec family and is optimized for 12-band Sentinel-2 imagery.
 
-See the paper for additional architectural and training details.
+See the [paper](https://arxiv.org/abs/2510.12670) for additional architectural and training details.
 
 ---
 
@@ -107,8 +110,8 @@ GitHub repository: https://github.com/IBM/TerraCodec
 If you use TerraCodec in your research, please cite:
 ```
 @article{terracodec2025,
-  title   = {TerraCodec: Neural Codecs for Earth Observation},
-  author  = {Costa Watanabe, Julen and Wittmann, Isabelle and Blumenstiel, Benedikt},
+  title   = {TerraCodec: Compressing Optical Earth Observation Data},
+  author  = {Costa Watanabe, Julen and Wittmann, Isabelle and Blumenstiel, Benedikt and Schindler, Konrad},
   journal = {arXiv preprint arXiv:2510.12670},
   year    = {2025}
 }