Update README.md

README.md

@@ -1,5 +1,6 @@
 ---
 license: apache-2.0
+base_model: hustvl/yolos-small
 tags:
 - object-detection
 - vision
@@ -8,6 +9,8 @@ tags:
 # Yolos-small-crowd
 
 YOLOS model fine-tuned on COCO 2017 object detection (118k annotated images). It was introduced in the paper [You Only Look at One Sequence: Rethinking Transformer in Vision through Object Detection](https://arxiv.org/abs/2106.00666) by Fang et al. and first released in [this repository](https://github.com/hustvl/YOLOS). 
+![model_image](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/yolos_architecture.png)
+
 
 ## Model description
 This model has been finetuned on the following [crowd-detection dataset](https://universe.roboflow.com/institut-teknologi-nasional-bandung-mxgtc/crowd-detection-i75bl) with the following results on the test set:
@@ -76,4 +79,30 @@ The following hyperparameters were used during training:
 - Transformers 4.36.2
 - pycocotools 2.0.7
 
-If you want to support me, you can [here](https://ko-fi.com/adamcodd).
+If you want to support me, you can [here](https://ko-fi.com/adamcodd).
+
+### BibTeX entry and citation info
+
+```bibtex
+@article{DBLP:journals/corr/abs-2106-00666,
+  author    = {Yuxin Fang and
+               Bencheng Liao and
+               Xinggang Wang and
+               Jiemin Fang and
+               Jiyang Qi and
+               Rui Wu and
+               Jianwei Niu and
+               Wenyu Liu},
+  title     = {You Only Look at One Sequence: Rethinking Transformer in Vision through
+               Object Detection},
+  journal   = {CoRR},
+  volume    = {abs/2106.00666},
+  year      = {2021},
+  url       = {https://arxiv.org/abs/2106.00666},
+  eprinttype = {arXiv},
+  eprint    = {2106.00666},
+  timestamp = {Fri, 29 Apr 2022 19:49:16 +0200},
+  biburl    = {https://dblp.org/rec/journals/corr/abs-2106-00666.bib},
+  bibsource = {dblp computer science bibliography, https://dblp.org}
+}
+```