Update README.md

README.md

@@ -1,5 +1,49 @@
 ---
 license: llama3.1
+datasets:
+- remyxai/vqasynth_spacellava
 ---
 
 ![image/png](https://cdn-uploads.huggingface.co/production/uploads/647777304ae93470ffc28913/Z7kEAxSxvpYkKNjBLm6GY.png)
+
+# Model Card for SpaceLLaVA
+
+**SpaceLlama3.1** uses [llama3.1-8B](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) as the llm backbone along with the fused DINOv2+SigLIP features of [prismatic-vlms](https://github.com/TRI-ML/prismatic-vlms) for a full fine-tune on a [dataset](https://huggingface.co/datasets/remyxai/vqasynth_spacellava) designed with [VQASynth](https://github.com/remyxai/VQASynth/tree/main) to enhance spatial reasoning as in [SpatialVLM](https://spatial-vlm.github.io/).
+
+
+## Model Details
+
+### Model Description
+
+This model uses data synthesis techniques and publically available models to reproduce the work described in SpatialVLM to enhance the spatial reasoning of multimodal models.
+With a pipeline of expert models, we can infer spatial relationships between objects in a scene to create VQA dataset for spatial reasoning.
+
+
+- **Developed by:** remyx.ai
+- **Model type:** MultiModal Model, Vision Language Model, Prismatic-vlms, Llama 3.1
+- **License:** Apache-2.0
+- **Finetuned from model:** Llama 3.1
+
+### Model Sources
+- **Dataset:** [SpaceLLaVA](https://huggingface.co/datasets/remyxai/vqasynth_spacellava)
+- **Repository:** [VQASynth](https://github.com/remyxai/VQASynth/tree/main)
+- **Paper:** [SpatialVLM](https://arxiv.org/abs/2401.12168)
+
+
+## Citation
+```
+@article{chen2024spatialvlm,
+  title = {SpatialVLM: Endowing Vision-Language Models with Spatial Reasoning Capabilities},
+  author = {Chen, Boyuan and Xu, Zhuo and Kirmani, Sean and Ichter, Brian and Driess, Danny and Florence, Pete and Sadigh, Dorsa and Guibas, Leonidas and Xia, Fei},
+  journal = {arXiv preprint arXiv:2401.12168},
+  year = {2024},
+  url = {https://arxiv.org/abs/2401.12168},
+}
+
+@inproceedings{karamcheti2024prismatic,
+  title = {Prismatic VLMs: Investigating the Design Space of Visually-Conditioned Language Models},
+  author = {Siddharth Karamcheti and Suraj Nair and Ashwin Balakrishna and Percy Liang and Thomas Kollar and Dorsa Sadigh},
+  booktitle = {International Conference on Machine Learning (ICML)},
+  year = {2024},
+}
+```