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README.md

@@ -22,19 +22,20 @@ WaLa-SK-1B is a large-scale 3D generative model trained on a massive dataset of
 - **Model type:** 3D Generative Model
 - **License:** Autodesk Non-Commercial (3D Generative) v1.0
 
-For more information please look at the [Project](TBD) [Page](TBD) and [the paper](TBD).
+For more information please look at the [Project Page](https://autodeskailab.github.io/WaLaProject) and [the paper](TBD).
 
 ### Model Sources
 
+- **Project Page:** [WaLa](https://autodeskailab.github.io/WaLaProject)
 - **Repository:** [Github](https://github.com/AutodeskAILab/WaLa)
 - **Paper:** [ArXiv:TBD](TBD)
-- **Demo:** [TBD](TBD)
+- **Demo:** [Colab](https://colab.research.google.com/drive/1W5zPXw9xWNpLTlU5rnq7g3jtIA2BX6aC?usp=sharing)
 
 ## Uses
 
 ### Direct Use
 
-This model is released by Autodesk and intended for academic and research purposes only for the theoretical exploration and demonstration of the WaLa 3D generative framework. Please see [here](TBD) for inferencing instructions. 
+This model is released by Autodesk and intended for academic and research purposes only for the theoretical exploration and demonstration of the WaLa 3D generative framework. Please see [here](https://github.com/AutodeskAILab/WaLa?tab=readme-ov-file#getting-started) for inferencing instructions. 
 
 ### Out-of-Scope Use
 
@@ -61,7 +62,7 @@ The model should not be used for:
 
 ## How to Get Started with the Model
 
-Please refer to the instructions [here](TBD)
+Please refer to the instructions [here](https://github.com/AutodeskAILab/WaLa?tab=readme-ov-file#getting-started)
 
 ## Training Details
 
@@ -84,29 +85,6 @@ Each 3D shape in the dataset was converted into a truncated signed distance func
 - The model contains approximately 956 million parameters.
 - The model can generate shapes within 2-4 seconds.
 
-## Evaluation
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-The model was evaluated on the Google Scanned Objects (GSO) dataset and a validation set from the training data (MAS validation data).
-
-#### Factors
-
-The evaluation considered various factors such as the quality of generated shapes, the ability to capture fine details and complex structures, and the model's performance across different object categories and sketch styles.
-
-#### Metrics
-
-The model was evaluated using the following metrics:
-- Intersection over Union (IoU)
-- Light Field Distance (LFD)
-- Chamfer Distance (CD)
-
-### Results
-
-[Specific results for the sketch-to-3D model to be added when available]
-
 ## Technical Specifications
 
 ### Model Architecture and Objective
@@ -117,7 +95,7 @@ The model uses a U-ViT architecture with modifications. It employs a wavelet-bas
 
 #### Hardware
 
-[TBD]
+The model was trained on NVIDIA H100 GPUs.
 
 ## Citation